Diaa Eldin Elshikha

Interests

Research

My research interests are crop water management, micro-irrigation, irrigation system design, deficit irrigation, and precision agriculture. My research goals are focused on optimization of irrigation systems, improving water application for maximum water use efficiency, irrigation scheduling techniques and models, adoption of low water use crops, and detection of crop water status through remote sensing and in-situ soil sensors.

Courses

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Scholarly Contributions

Journals/Publications

• Elsadek, E. A., Attalah, S., Williams, C., Thorp, K. R., Wang, D., & Elshikha, D. E. (2026). Comparing Cotton ET Data from a Satellite Platform, In Situ Sensor, and Soil Water Balance Method in Arizona. Agriculture (Switzerland), 16(Issue 2). doi:10.3390/agriculture16020228
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  Crop production in the desert Southwest of the United States, as well as in other arid and semi-arid regions, requires tools that provide accurate crop evapotranspiration (ET) estimates to support efficient irrigation management. Such tools include the web-based OpenET platform, which provides real-time ET data generated from six satellite-based models, their Ensemble, and a field-based system (LI-710, LI-COR Inc., Lincoln, NE, USA). This study evaluated simulated ET (ETSIM) of cotton (Gossypium hirsutum L.) derived from OpenET models (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, and SSEBop), their Ensemble approach, and LI-710. Field data were utilized to estimate cotton ET using the soil water balance (SWB) method (ETSWB) from June to October 2025 in Gila Bend, AZ, USA. Four evaluation metrics, the normalized root-mean-squared error (NRMSE), mean bias error (MBE), simulation error (Se), and coefficient of determination (R2), were employed to evaluate the performance of OpenET models, their Ensemble, and the LI-710 in estimating cotton ET. Statistical analysis indicated that the ALEXI/DisALEXI, geeSEBAL, and PT-JPL models substantially underestimated ETSWB, with simulation errors ranging from −26.92% to −20.57%. The eeMETRIC, SIMS, SSEBop, and Ensemble provided acceptable ET estimates (22.57% ≤ NRMSE ≤ 29.85%, −0.36 mm. day−1 ≤ MBE ≤ 0.16 mm. day−1, −7.58% ≤ Se ≤ 3.42%, 0.57 ≤ R2 ≤ 0.74). Meanwhile, LI-710 simulated cotton ET acceptably with a slight tendency to overestimate daily ET by 0.21 mm. A strong positive correlation was observed between daily ETSIM from LI-710 and ETSWB, with Se and NRMSE of 4.40% and 23.68%, respectively. Based on our findings, using a singular OpenET model, such as eeMETRIC, SIMS, or SSEBop, the OpenET Ensemble, and the LI-710 can offer growers and decision-makers reliable guidance for efficient irrigation management of late-planted cotton in arid and semi-arid climates.
• Attalah, S., Elsadek, E. A., Waller, P., Hunsaker, D. J., Thorp, K. R., Bautista, E., Williams, C., Wall, G., Orr, E., & Elshikha, D. E. (2025). Evaluation and comparison of OpenET models for estimating soil water depletion of irrigated alfalfa in Arizona. Agricultural Water Management, 320(Issue). doi:10.1016/j.agwat.2025.109850
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  Growers in arid regions often estimate soil water depletion (Dr) of the root zone in making irrigation scheduling decisions. While growers might use soil water sensors, actual Dr in fields may be only vaguely assessed. In this study, daily crop evapotranspiration (ETsat) data from the six OpenET satellite-based models (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, SSEBop) and the OpenET ensemble were incorporated into a soil water balance (SWB) to estimate Dr (Dr sat) for alfalfa (Medicago sativa L.) within a 46-ha, center-pivot field in Buckeye, Arizona. A daily SWB for each model input the average ETsat data acquired at four locations for both 30-m and 90-m pixel sizes, assuming an alfalfa root-zone of 1.8-m. Net irrigation (In) inputs were based on gross irrigation amounts, modified for evaporation losses using weather data from the AZMET station in Buckeye. Dr sat values were compared to the average observed root-zone Dr (Dr obs), as determined at the four locations by neutron moisture meter measurements on 21 dates between 05/23/2023 and 12/11/2023. Cumulative values were 841 mm for In plus effective precipitation, 776 mm (ALEXI/DisALEXI) to 1130 mm (SSEBop) for ETsat, and 816 mm of ET obtained by a seasonal SWB (ETswb) based on the average change in Dr obs (ΔDr obs) from first to last measurements. Average Dr obs fluctuated between 59 and 133 mm, and ΔDr obs was −25.0 ± 42.0 mm. Model variations in ETsat resulted in different estimates of Dr sat and agreements, where mean bias error (MBE) ranged from ≈ -35 % (PT-JPL) to 195 % (SSEBop). Despite notable uncertainties in the SWB parameters and observed data, the SWB based on both the ensemble and ALEXI/DisALEXI ETsat capably tracked Dr obs for most of the observations, excluding those made from late-July to mid-August. However, the best overall agreement was with the ensemble data, where differences between cumulative ETsat and ETswb and ΔDr sat and ΔDr obs were small, and MBE for Dr sat was less than 9 % and 15 % at 30-m and 90-m pixels, respectively. Findings suggest that using the single value OpenET ensemble daily ET could be a reliable source for estimating the Dr in arid climate alfalfa fields.
• Elsadek, E. A., Ali, M. A., Williams, C., Thorp, K. R., & Elshikha, D. E. (2025). A Novel Framework for Predicting Daily Reference Evapotranspiration Using Interpretable Machine Learning Techniques. Agriculture (Switzerland), 15(Issue 18). doi:10.3390/agriculture15181985
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  Accurate estimation of daily reference evapotranspiration (ETo) is crucial for sustainable water resource management and irrigation scheduling, especially in water-scarce regions like Arizona. The standardized Penman–Monteith (PM) method is costly and requires specialized instruments and expertise, making it generally impractical for commercial growers. This study developed 35 ETo models to predict daily ETo across Coolidge, Maricopa, and Queen Creek in Pinal County, Arizona. Seven input combinations of daily meteorological variables were used for training and testing five machine learning (ML) models: Artificial Neural Network (ANN), Random Forest (RF), Extreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and Support Vector Machine (SVM). Four statistical indicators, coefficient of determination (R2), the normalized root-mean-squared error (RMSEn), mean absolute error (MAE), and simulation error (Se), were used to evaluate the ML models’ performance in comparison with the FAO-56 PM standardized method. The SHapley Additive exPlanations (SHAP) method was used to interpret each meteorological variable’s contribution to the model predictions. Overall, the 35 ETo-developed models showed an excellent to fair performance in predicting daily ETo over the three weather stations. Employing ANN10, RF10, XGBoost10, CatBoost10, and SVM10, incorporating all ten meteorological variables, yielded the highest accuracies during training and testing periods (0.994 ≤ R2 ≤ 1.0, 0.729 ≤ RMSEn ≤ 3.662, 0.030 ≤ MAE ≤ 0.181 mm·day−1, and 0.833 ≤ Se ≤ 2.295). Excluding meteorological variables caused a gradual decline in ET-developed models’ performance across the stations. However, 3-variable models using only maximum, minimum, and average temperatures (Tmax, Tmin, and Tave) predicted ETo well across the three stations during testing (17.655 ≤ RMSEn ≤ 13.469 and Se ≤ 15.45%). Results highlighted that Tmax, solar radiation (Rs), and wind speed at 2 m height (U2) are the most influential factors affecting ETo at the central Arizona sites, followed by extraterrestrial solar radiation (Ra) and Tave. In contrast, humidity-related variables (RHmin, RHmax, and RHave), along with Tmin and precipitation (Pr), had minimal impact on the model’s predictions. The results are informative for assisting growers and policymakers in developing effective water management strategies, especially for arid regions like central Arizona.
• Elsadek, E. A., Attalah, S., Waller, P., Norton, R., Hunsaker, D. J., Williams, C., Thorp, K. R., Orr, E., & Elshikha, D. E. (2025). Simulating Water Use and Yield for Full and Deficit Flood-Irrigated Cotton in Arizona, USA. Agronomy, 15(Issue 9). doi:10.3390/agronomy15092023
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  Improved irrigation guidelines are needed to maximize crop water use efficiency. Combining field data with simulation models can provide information for better irrigation management. The objective of the present study was to evaluate the effects of two flood irrigation treatments on fiber yield (FY) and quality during the 2023 and 2024 growing seasons in Maricopa, Arizona, USA. Two irrigation treatments, denoted as F100% and F80%, were arranged in a randomized complete block design with three replicates. Then, AquaCrop was used to simulate cotton yield (YTot), water use (ETobs), and total soil water content (WCTot) for the two irrigation treatments. Six statistical metrics, including the coefficient of determination (R2), the normalized root-mean-square error (NRMSE), the mean absolute error (MAE), simulation error (Se), the index of agreement (Dindex), and the Nash–Sutcliffe efficiency coefficient (NSE), were employed to assess model performance. The results of the field trial demonstrated that reducing the irrigation rate to 80% of ETc negatively impacted cotton FY and ET water productivity (ETWP); the FY declined by 45.2% (ETWP = 0.097 kg·ha−1) in 2023 and by 38.1% (ETWP = 0.133 kg·ha−1) in 2024. Conversely, F100% produced a more uniform and stronger fiber than F80%, with the uniformity index (UI) and fiber strength (STR) measuring 81.7% and 29.5 g tex−1 in 2023 and 82.2% and 30.0 g tex−1 in 2024, indicating that UI and STR were well correlated with soil water during both growing seasons. AquaCrop showed an excellent performance in simulating cotton CC during the two growing seasons. The R2, NRMSE, Dindex, and NSE were between 0.97 and 0.99, 8.45% and 14.36%, 0.98 and 0.99, and 0.96 and 0.98, respectively. Moreover, the AquaCrop model accurately simulated YTot during these seasons, with R2, NRMSE, Dindex, and NSE for pooled yield data of 0.93, 8.05%, 0.95, and 0.78, respectively. The model consistently overestimated YTot, ETobs, and WCTot, but within an acceptable Se (Se < 15%) during both growing seasons, except for WCTot under the 80% treatment in 2023 (Se = 26.4%). Consequently, AquaCrop can be considered an effective tool for irrigation management and yield prediction in arid climates such as Arizona.
• Elsadek, E. A., Elshikha, D. E., Awad, A., Hamoud, Y. A., Elsheikha, A. M., Williams, C., Orr, E., Shaghaleh, H., Hamad, A. A., Thorp, K. R., & Elbeltagi, A. (2025). Projecting rice water footprint for different shared socioeconomic pathways under arid climate conditions. Irrigation Science, 43(Issue 4). doi:10.1007/s00271-025-01019-8
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  Climate change would intensify water and food scarcity in arid regions. As a main cereal crop, projecting rice water consumption and yield responses to climate change is crucial for improving water management and ensuring food security. This study projected the effect of climate change on rice yield (Y), evapotranspiration (ET), and total water footprint (WFT) in Damietta, Egypt, under two Shared Socioeconomic Pathways (SSPs): 2–4.5 and 5–8.5. First, five global climate models (GCMs) were evaluated for their accuracy in capturing the baseline temperatures (T) and precipitation (Pr) under the SSPs scenarios. Then, AquaCrop-GIS, integrated with ensemble downscaled GCMs data, was used to project the future climate change impacts on rice Y, ET, and WFT under a 3-day irrigation frequency regime (3IF) and two SSPs and CO2 emission scenarios during 2021–2099. Results indicated that GCMs accurately predicted climate variables during the baseline. Without CO2 effect, Y would slightly increase (1.07%–3.03%) during the 2030s and 2050s but significantly decline (4.55%–18.94%) during the 2070s and 2090s under the SSPs scenarios. However, with CO2 effect, Y would significantly increase (14.19%–28.31%) during 2021–2099. Projected ET would decline (1.42%–18.98%) under the SSPs and CO2 scenarios over time. Meanwhile, without CO2 effect, the WFT would increase by 2.88% to 17.13% during the 2070s and 2090s. However, with CO2 effect, the WFT would decrease significantly (15.45%–34.50%) under the SSPs scenarios during the future periods. The findings help growers and policymakers develop effective water management strategies for agricultural sustainability in arid regions.
• Chen, Y., Dierig, D., Wang, G., Elshikha, D., Ray, D., Maier, R., Neilson, J., & Barberán, A. (2024). Identifying critical microbes in guayule-microbe and microbe-microbe associations. Plant and Soil, 494(1-2), 269-284. doi:10.1007/s11104-023-06269-z
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  Background: Plant-microbe associations play central roles in ecosystem functioning, with some critical microbes significantly influencing the growth and health of plants. Additionally, some microbes are highly associated with other microbes in either competitive or cooperative microbe-microbe associations. Here, we aimed to determine whether there is overlap between critical microbes in plant-microbe and microbe-microbe associations by using guayule (a rubber-producing crop) as a model plant. Methods: Using marker gene amplicon sequencing, we characterized the bacterial/archaeal and fungal communities in soil samples collected from a guayule agroecosystem at six time points that represent changes in guayule productivity and growth stage. The critical microbes in guayule-microbe associations were phylotypes whose relative abundances were positively (positive taxa) or negatively (negative taxa) associated with guayule productivity. Network analysis was used to identify the critical microbes in microbe-microbe associations. Results: Some positive taxa in guayule-microbe associations were ammonia-oxidizing archaea (AOA) and bacteria (AOB) and arbuscular mycorrhizal fungi (AMF), and negative taxa included some microbes resistant to aridity. Some of the critical microbes in microbe-microbe associations were fungal plant pathogens. There were 9 phylotypes representing the overlap between critical microbes in guayule-microbe and microbe-microbe associations. This overlap group included AOB, phototrophic bacteria, AMF, and saprotrophic fungi, along with unique taxa of unknown function. Conclusions: Our study highlighted the association of the soil microbiome with the growth and health of guayule. Our systematic approach narrowed down the immense number of microbial taxa to a ‘most wanted’ list that we define as critical to the entire guayule agroecosystem.
• Chen, Y., Dierig, D. A., Wang, G., Elshikha, D. M., Ray, D. T., Barberán, A., Maier, R. M., & Neilson, J. W. (2023). Identifying critical microbes in guayule‑microbe and microbe‑microbe associations. Plant and Soil. doi:https://doi.org/10.1007/s11104-023-06269-z
• Elshikha, D. E., Waller, P. M., Hunsaker, D. J., Thorp, K. R., Wang, G., Dierig, D., Cruz, V. M., Attalah, S., Katterman, M. E., Williams, C., Ray, D. T., Norton, R., Orr, E., Wall, G. W., & Ogden, K. L. (2023). Water Use, Growth, and Yield of Ratooned Guayule under Subsurface Drip and Furrow Irrigation in the US Southwest Desert. Water (Switzerland), 15(Issue 19). doi:10.3390/w15193412
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  Guayule (Parthenium argentatum, A. Gray) is a perennial desert shrub with ratoon-cropping potential for multiple harvests of its natural rubber, resin, and bagasse byproducts. However, yield expectations, water use requirements, and irrigation scheduling information for ratooned guayule are extremely limited. The objectives of this study were to evaluate dry biomass (DB), contents of rubber (R) and resin (Re) and yields of rubber (RY) and resin (ReY) responses to irrigation treatments, and develop irrigation management criteria for ratooned guayule. The water productivity (WP) of the yield components were also evaluated. Guayule plants that were direct-seeded in April 2018 were ratooned and regrown starting in April 2020, after an initial 2-year harvest at two locations in Arizona: Maricopa and Eloy on sandy loam and clay soils, respectively. Plots were irrigated with subsurface drip irrigation (SDI) at 50, 75, and 100% replacement of crop evapotranspiration (ETc), respectively, and furrow irrigation at 100% ETc replacement, as determined by soil water balance measurements. The Eloy location did not include the 100% irrigation treatment under SDI due to unsuccessful regrowth for this specific treatment. The irrigation treatments at the locations were replicated three times in a randomized complete block design. After 21–22 months of regrowth, the guayule plants were harvested in plots. The results showed that DB increased with the amount of total water applied (TWA, irrigation plus precipitation), while R and Re were reduced at the highest TWA received at both locations. Ultimately, the SDI treatments with 75% ETc replacement resulted in the best irrigation management in terms of maximizing RY and ReY, and WP for both locations and soil types. Compared to the initial 2-year direct-seeded guayule crop, ratooned guayule required less TWA and attained higher DB, RY, and ReY, as well as higher WP, with average increases of 25% in dry biomass, 33% in rubber yield, and 32% in resin yield. A grower’s costs for planting the initial direct-seeded guayule crop would be offset by the additional yield revenue of the ratooned crop, which would have comparatively small startup costs.
• Elshikha, D. E., Wang, G., Waller, P. M., Hunsaker, D. J., Dierig, D., Thorp, K. R., Thompson, A., Katterman, M. E., Herritt, M. T., Bautista, E., Ray, D. T., & Wall, G. W. (2023). Guayule growth and yield responses to deficit irrigation strategies in the U.S. desert. Agricultural Water Management, 277(Issue). doi:10.1016/j.agwat.2022.108093
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  Deficit irrigation can maximize the water productivity (WP) of guayule and increase the percent rubber (%R) in shrubs compared to irrigation meeting full crop evapotranspiration (ETc). In this study, we hypothesize that certain deficit irrigation strategies that impose soil water deficits during specific periods of growth or throughout the growing season might produce higher %R and equivalent rubber yield (RY), thereby, increasing WP compared to full irrigation. Herein, growth and yield responses of direct-seeded guayule to different water deficit schemes were evaluated in an experiment on a silty clay loam soil, in a field in central Arizona using furrow irrigation. Two guayule cultivars (AZ2 and AZ6) were grown for 22.5 months (Apr. 2020-Mar. 2022) in a split-plot design, with six irrigation treatments in whole plots and cultivars in split-plots. After homogeneous irrigation for two months, irrigation treatments were begun. A control treatment was irrigated to meet full ETc. The other five treatments were irrigated with less water using various deficit irrigation strategies imposed during the two-year growing period. Measurements included plant height (h), cover fraction (fc), soil water contents, harvest of dry biomass (DB), RY, resin yield (ReY), %R, and percent resin (%Re). Total water applied (TWA) by irrigation and precipitation to treatments varied from 2780 to 1084 mm and DB varied from 20.5 to 9.1 Mg ha−1. The h and fc were significantly greater at higher irrigation levels, while they were also significantly greater in AZ6 than AZ2. The DB, RY, and ReY generally increased linearly with TWA. However, it was found that a treatment applying every other irrigation of the control resulted in statistically equivalent yields to the control, with 36% less irrigation. The %R generally decreased with TWA, while %Re did not change. However, DB, %R, and %Re were significantly greater for AZ2 than AZ6, as were RY, ReY, and WP. Among the deficit treatments evaluated, every other irrigation offers the best strategy to significantly increase guayule WP without causing a yield penalty.
• Elshikha, D. M., Waller, P. M., Hunsaker, D. J., Thorp, K. R., Wang, G., Dierig, D., Cruz, V. M., Attalah, S., Katterman, M. E., Williams, C., Ray, D. T., Norton, R., Orr, E., Wall, G. W., & Ogden, K. L. (2023). Water Use, Growth, and Yield of Ratooned Guayule under Subsurface Drip and Furrow Irrigation in the US Southwest Desert. . Water, 15 (19). doi:https://doi.org/10.3390/w15193412
• Elshikha, D. M., Wang, G., Waller, P. M., Hunsaker, D. J., Dierig, D., Thorp, K. R., Thompson, A. L., Katterman, M. E., Herritt, M. T., Bautista, E., Ray, D. T., & Wall, G. W. (2023). Guayule growth and yield responses to deficit irrigation strategies in the U.S. desert. Agricultural Water Management, 277, 108093.
• Katterman, M. E., Waller, P. M., Elshikha, D. E., Wall, G. W., Hunsaker, D. J., Loeffler, R. S., & Ogden, K. L. (2023). WINDS Model Simulation of Guayule Irrigation. Water (Switzerland), 15(Issue 19). doi:10.3390/w15193500
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  The WINDS (Water-Use, Irrigation, Nitrogen, Drainage, and Salinity) model uses the FAO56 dual crop coefficient and a daily time-step soil–water balance to simulate evapotranspiration and water content in the soil profile. This research calibrated the WINDS model for simulation of guayule under full irrigation. Using data from a furrow irrigated two-season guayule experiment in Arizona, this research developed segmented curves for guayule basal crop coefficient, canopy cover, crop height and root growth. The two-season guayule basal crop coefficient (Kcb) curve included first and second season development, midseason, late-season and end-season growth stages. For a fully irrigated guayule crop, the year one midseason Kcb was 1.14. The second year Kcb development phase began after the crop was semi-dormant during the first winter. The second year Kcb value was 1.23. The two-season root growth curve included a growth phase during the first season, no growth during winter, and a second growth phase during the second winter. A table allocated fractions of total transpiration to soil layers as a function of root depth. With the calibrated tables and curves, the WINDS model simulated soil moisture content with a root mean squared error (RMSE) of 1- to 3-% volumetric water content in seven soil layers compared with neutron probe water contents during the two-year growth cycle. Thus, this research developed growth curves and accurately simulated evapotranspiration and water content for a two-season guayule crop.
• Katterman, M. E., Waller, P. M., Elshikha, D. M., Wall, G. W., Hunsaker, D. J., Loeffler, R. S., & Ogden, K. L. (2023). WINDS Model Simulation of Guayule Irrigation. Water, 15 (19), 3500. doi:https://doi.org/10.3390/w15193500
• Loeffler, R. S., Elshikha, D. E., French, A., Thorp, K. R., Waller, P. M., Hunsaker, D. J., & Maqsood, H. (2023). WINDS model demonstration with field data from a furrow-irrigated cotton experiment. Water Journal, 15(8), 15.
• Maqsood, H., Hunsaker, D. J., Waller, P., Thorp, K. R., French, A., Elshikha, D. E., & Loeffler, R. (2023). WINDS Model Demonstration with Field Data from a Furrow-Irrigated Cotton Experiment. Water (Switzerland), 15(Issue 8). doi:10.3390/w15081544
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  The WINDS (Water-Use, Irrigation, Nitrogen, Drainage, and Salinity) model was developed to provide decision support for irrigated-crop management in the U.S. Southwest. The model uses a daily time-step soil water balance (SWB) to simulate the dynamics of water content in the soil profile and evapotranspiration. The model employs a tipping bucket approach during infiltration events and Richards’ equation between infiltration events. This research demonstrates WINDS simulation of a furrow-irrigated cotton experiment, conducted in 2007 in central Arizona, U.S. Calibration procedures for WINDS include the crop coefficient curve or segmented crop coefficient curve, rate of root growth, and root activity during the growing season. In this research, field capacity and wilting point were measured in the laboratory at each location and in each layer. Field measurements included water contents in layers by neutron moisture meter (NMM), irrigation, crop growth, final yield, and actual ETc derived by SWB. The calibrated WINDS model was compared to the neutron probe moisture contents. The average coefficient of determination was 0.92, and average root mean squared error (RMSE) was 0.027 m3 m−3. The study also demonstrated WINDS ability to reproduce measured crop evapotranspiration (ETc actual) during the growing season. This paper introduces the online WINDS model.
• Maqsood, H., Hunsaker, D. J., Waller, P., Thorp, K. R., French, A., Elshikha, D. M., & Loeffler, R. S. (2023). WINDS Model Demonstration with Field Data from a Furrow-Irrigated Cotton Experiment. Water, 15 (8), 1544. doi:https://doi.org/10.3390/w15081544
• Ogden, K. L., Loeffler, R. S., Hunsaker, D. J., Wall, G. W., Elshikha, D. E., Waller, P. M., & Katterman, M. E. (2023). WINDS model simulation of guayule irrigation. Water Journal, 15(19), 15.
• Ogden, K. L., Wall, G. W., Orr, E. R., Norton, E. R., Ray, D. T., Williams, C., Katterman, M. E., Attalah, S., Cruz, V. V., Dierig, D., Wang, G., Thorp, K. R., Hunsaker, D. J., Waller, P. M., Elshikha, D. E., Ogden, K. L., Loeffler, R. S., Hunsaker, D. J., Wall, G. W., , Elshikha, D. E., et al. (2023).

  Water Use, Growth, and Yield of Ratooned Guayule under Subsurface Drip and Furrow Irrigation in the US Southwest Desert

  . Water Journal, 15(19), 15.
• Orr, E., Masson, R., Sanyal, D., & Elshikha, D. M. (2023). Surviving these drying times: The role of a desert agricultural extension agent in helping farmers face drought. . JOURNAL OF THE NACAA, 16 (2).
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  A publication to describe the role of a desert agricultural extension agent in helping farmers face drought
• Wang, G., Elshikha, D. E., Katterman, M. E., Sullivan, T., Dittmar, S. H., Cruz, V. M., Hunsaker, D. J., Waller, P., Ray, D. T., & Dierig, D. A. (2022). Irrigation effects on seasonal growth and rubber production of direct-seeded guayule. Industrial Crops and Products. doi:10.1016/j.indcrop.2021.114442
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  Understanding guayule’s response to environmental factors, such as location, soil type, drought stress, and seasonal growth variation is critical for irrigation management to maximize and estimate rubber and resin accumulation throughout the growing seasons. A study was conducted at two sites with different soil types (sandy loam soil at Maricopa, AZ and a clay soil at Eloy, AZ) to compare plant growth and rubber accumulation among different irrigation treatments during a two-year growing season. The above- and below-ground biomass, biomass growth, rubber/resin content, and rubber/resin accumulation were measured every other month from establishment to final harvest in well-watered treatments, which received 100% replacement of crop evapotranspiration (ETc) and irrigated with subsurface drip and furrow (denoted as D100 and F100, respectively), and compared to reduced irrigation treatments (D50 and F50), which received 50% replacement of ETc. Drip irrigation with high water input (D100) decreased root mass partition, but leaf, stem, and flower partitions were not significantly affected by irrigation treatment. Biomass yield was higher in the well-watered treatments as expected, while rubber and resin content were lower, indicating rubber and resin dilution by higher biomass. For all treatments, rubber and resin yield increased linearly over the two-year growing season. However, the rates of increase were different among the irrigation treatments. The D100 treatment had a higher rubber yield increase rate compared to F100 and D50 in sandy loam soil at Maricopa, while the D100 treatment had the lowest increase rate compared to the F100, F50, and D50 treatments in clay soil at Eloy. Top branches of guayule plants in the D100 treatment at Eloy lodged in the second year and likely contributed to lower rubber content and rubber yield in the treatment. The drip irrigation treatments D50 and D100 had higher water productivity for rubber yield at Maricopa. However, the D50 and F50 treatment had the highest water productivity for guayule rubber yield, while the D100 treatment had the lowest due to lower rubber content at Eloy. Root rubber content was 31–39% lower than stem at the two locations. This study indicates that rubber biosynthesis occurred in guayule year-round and that it is possible in clay soils to reduce irrigation without a significant loss in rubber yield.
• Wang, G., Elshikha, D., Katterman, M., Sullivan, T., Dittmar, S., Cruz, V., Hunsaker, D., Waller, P., Ray, D., & Dierig, D. (2022). Irrigation effects on seasonal growth and rubber production of direct-seeded guayule. Industrial Crops and Products, 177. doi:10.1016/j.indcrop.2021.114442
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  Understanding guayule's response to environmental factors, such as location, soil type, drought stress, and seasonal growth variation is critical for irrigation management to maximize and estimate rubber and resin accumulation throughout the growing seasons. A study was conducted at two sites with different soil types (sandy loam soil at Maricopa, AZ and a clay soil at Eloy, AZ) to compare plant growth and rubber accumulation among different irrigation treatments during a two-year growing season. The above- and below-ground biomass, biomass growth, rubber/resin content, and rubber/resin accumulation were measured every other month from establishment to final harvest in well-watered treatments, which received 100% replacement of crop evapotranspiration (ETc) and irrigated with subsurface drip and furrow (denoted as D100 and F100, respectively), and compared to reduced irrigation treatments (D50 and F50), which received 50% replacement of ETc. Drip irrigation with high water input (D100) decreased root mass partition, but leaf, stem, and flower partitions were not significantly affected by irrigation treatment. Biomass yield was higher in the well-watered treatments as expected, while rubber and resin content were lower, indicating rubber and resin dilution by higher biomass. For all treatments, rubber and resin yield increased linearly over the two-year growing season. However, the rates of increase were different among the irrigation treatments. The D100 treatment had a higher rubber yield increase rate compared to F100 and D50 in sandy loam soil at Maricopa, while the D100 treatment had the lowest increase rate compared to the F100, F50, and D50 treatments in clay soil at Eloy. Top branches of guayule plants in the D100 treatment at Eloy lodged in the second year and likely contributed to lower rubber content and rubber yield in the treatment. The drip irrigation treatments D50 and D100 had higher water productivity for rubber yield at Maricopa. However, the D50 and F50 treatment had the highest water productivity for guayule rubber yield, while the D100 treatment had the lowest due to lower rubber content at Eloy. Root rubber content was 31–39% lower than stem at the two locations. This study indicates that rubber biosynthesis occurred in guayule year-round and that it is possible in clay soils to reduce irrigation without a significant loss in rubber yield.
• Wall, G. W., Bronson, K. F., Katterman, M. E., Thorp, K. R., Cruz, V. M., Wang, G., Dierig, D. A., Hunsaker, D. J., Waller, P., & Elshikha, D. E. (2021). Growth, water use, and crop coefficients of direct-seeded guayule with furrow and subsurface drip irrigation in Arizona. Industrial Crops and Products. doi:10.1016/j.indcrop.2021.113819
• Andrade-Sanchez, P., Pauli, D., French, A. S., Elshikha, D. E., Conley, M. P., Thorp, K. R., & Thompson, A. (2019). Comparing Nadir and Multi-Angle View Sensor Technologies for Measuring in-Field Plant Height of Upland Cotton. Remote Sensing. doi:10.3390/rs11060700
• Hunsaker, D., Elshikha, D., & Bronson, K. (2019). High guayule rubber production with subsurface drip irrigation in the US desert Southwest. Agricultural Water Management, 220, 1-12. doi:10.1016/j.agwat.2019.04.016
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  Guayule is being produced for natural rubber in US desert areas, where irrigation requirements are high. Improved irrigation practices and methods are required to increase guayule yields and reduce its water use. Presently, there is no information available on guayule produced using subsurface drip irrigation (SDI). Therefore, we conducted an SDI guayule field study in 2012–2015 in Maricopa, Arizona, US. The objectives were to evaluate guayule dry biomass (DB), rubber yield (RY), and crop evapotranspiration (ETc) responses to water application level, and to compare these results to previously reported guayule irrigation studies. Guayule seedlings were transplanted in the field in October 2012 at 0.35-m spacing, in 100-m long rows, spaced 1.02 m apart. The field had 15, 8-row wide plots (5 irrigation treatments x 3 replicates). Irrigation treatments were imposed in a randomized complete block design starting in May 2013. Irrigation scheduling was based on the measured soil water depletion percentage (SWDp) of a fully-irrigated treatment, defined as 100% ETc replacement, and maintained at ≈20-35% SWDp. The other treatments received 25%, 50%, 75%, and 125% of irrigation applied to the 100% treatment on each day of irrigation. Destructive samples for dry biomass, rubber, and resin contents were periodically taken from each plot between February and November of each year until the guayule was bulk-harvested in March 2015. Results indicated ETc, DB, and RY increased with total water applied (irrigation + rain), which varied between treatments from 2080 to 4900 mm for the 29-month growing season. Final dry biomass and rubber yields of 61.2 Mg/ha and 3430 kg/ha, respectively, were achieved with the highest irrigation treatment level (125%) and these yields were significantly higher than those under all other irrigation levels. All SDI irrigation treatments except for the lowest 25% level had rubber yields from 24 to 200% greater than the maximum RY achieved under a companion surface irrigation study conducted simultaneously in Maricopa.
• Pauli, D., Hunsaker, D. J., Elshikha, D. E., Pugh, N. A., Ilut, D. C., McMahan, C. M., Ponciano, G., & Nelson, A. D. (2019). Transcriptomic and evolutionary analysis of the mechanisms by which P. argentatum, a rubber producing perennial, responds to drought. BMC Plant Biology. doi:10.1186/s12870-019-2106-2
• Eranki, P. L., El-Shikha, D., Hunsaker, D. J., Bronson, K. F., & Landis, A. E. (2017). A comparative life cycle assessment of flood and drip irrigation for guayule rubber production using experimental field data. Industrial Crops and Products, 99(Issue). doi:10.1016/j.indcrop.2017.01.020
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  Guayule (Parthenium argentatum) is a woody, perennial desert shrub, native to the arid American Southwest. It produces natural rubber that can be used to replace Hevea natural rubber for U.S. domestic rubber demands. Irrigation water application and practices form an important component of its agricultural cultivation process. A comparative gate-to-gate lifecycle assessment (LCA) was conducted to examine two different irrigation practices in guayule rubber production-blocked furrow irrigation (denoted as flood) and sub-surface drip irrigation (SDI, denoted as drip). In flood irrigation, furrows are used to convey water flooded from one end of the field. In drip irrigation, the plant is irrigated more frequently with lighter amounts using drip tapes buried beneath crop rows. All relevant field data to conduct the LCA were obtained from experimental plots in Maricopa, AZ. This study, the first of its kind for guayule, compares the metrics of energy consumption, lifecycle environmental impacts and irrigation water productivity. Drip irrigation showed a more efficient use of the applied water by generating higher rubber (46%) and bagasse (dry matter) yields (49%) compared to flood irrigation. Percent change calculations (with drip irrigation as the reference), showed that as a result of greater efficiency of water application in the drip irrigation system, it has between close-to-equal to 51% lower environmental impacts in various categories (with 23% lower impacts averaged over all impact categories). On the other hand, drip irrigation showed 13% higher energy consumption than flood because of the additional burdens of water pumping. Whereas water application was the foremost contributor to impact burdens in both flood and drip irrigations, the additional burdens of water pumping and sulfuric acid use for maintaining blockage-free drip tape were also noteworthy in the drip system. Experimental field operations were the central contributor to energy consumption in both irrigation methods. By separating a crucial stage of guayule production, namely irrigation, connections emerge between various key parameters in the two irrigation methods; accordingly, the outcomes from the evaluation of these two irrigation systems can assist with decision-making in the lifecycle framework of guayule rubber production.
• Hunsaker, D. J., & Elshikha, D. M. (2017). Surface irrigation management for guayule rubber production in the US desert Southwest. Agricultural Water Management, 185(Issue). doi:10.1016/j.agwat.2017.01.015
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  Agricultural production of the desert shrub, guayule (Parthenium argentatum G.), requires judicious management of irrigation water for achieving economic yields and high water productivity. This study expands existing, but limited and dated knowledge on irrigation management of guayule. A 29-month guayule surface irrigation study (Oct. 2012–Mar. 2015) in Maricopa, Arizona, US, imposed five irrigation treatments whose irrigation amounts were 40, 60, 80, 100, and 120% of irrigation applied to the 100% treatment, based on the soil water depletion (SWD) of the 100%. Irrigation treatments and soil water balance measurements began in Apr. 2013, ≈ 6 mos. after plant establishment. Measured SWD percentage prior to irrigation for the 100% treatment averaged 59%. The total water applied (TWA), irrigation and rain from planting to final harvest, varied from 2370 to 4720 mm. Cumulative ETc measured only over the final 23 months of the study (Apr. 2013 through Mar. 2015) varied from 1740 to 3720 mm. At final harvest, dry biomass (DB) varied from 15.7 to 27.9 Mg/ha, rubber yield (RY) from 1220 to 1680 kg/ha, and resin yield from 1290 to 2720 kg/ha. The study confirms that both DB and RY respond linearly to TWA. For maximum rubber yield using surface irrigation, it is recommended to use a SWD of 50% for irrigation scheduling and apply ≈2000 mm/year of total water. However, guayule water productivity (yield per unit TWA) can be significantly increased by reducing TWA by 25% (i.e., 1460 mm/year). This irrigation rate achieved 92% of the maximum RY in this study.
• Hunsaker, D. J., French, A. N., Clarke, T. R., & El-Shikha, D. M. (2011). Water use, crop coefficients, and irrigation management criteria for camelina production in arid regions. Irrigation Science, 29(Issue 1). doi:10.1007/s00271-010-0213-9
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  Camelina sativa (L.) Crantz is an oilseed crop touted as being suitable for production in the arid southwestern USA. However, because any significant development of the crop has been limited to cooler, rain-fed climate-areas, information and guidance for managing irrigated-camelina are lacking. This study measured the crop water use of a November-through-April camelina crop in Arizona using frequent measurements of soil water contents. The crop was grown under surface irrigation using five treatment levels of soil water depletion. The seed yields of treatments averaged 1,142 kg ha-1 (8.0% seed moisture) and were generally comparable with camelina yields reported in other parts of the USA. Varying total irrigation water amounts to treatments (295-330 mm) did not significantly affect yield, whereas total crop evapotranspiration (ETc) was increased for the most frequently irrigated treatment. However, total ETc for the camelina treatments (332-371 mm) was markedly less than that typically needed by grain and vegetable crops (600-655 mm), which are commonly grown during the same timeframe in Arizona. The camelina water-use data were used to develop crop coefficients based on days past planting, growing degree days, and canopy spectral reflectance. The crop coefficient curves, along with information presented on camelina soil water depletion and root zone water extraction characteristics will provide camelina growers in arid regions with practical tools for managing irrigations. © 2010 US Government.
• Hunsaker, D. J., El-Shikha, D. M., Clarke, T. R., French, A. N., & Thorp, K. R. (2009). Using ESAP software for predicting the spatial distributions of NDVI and transpiration of cotton. Agricultural Water Management, 96(Issue 9). doi:10.1016/j.agwat.2009.04.014
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  Observations of the normalized difference vegetation index (NDVI) from aerial imagery can be used to infer the spatial variability of basal crop coefficients (Kcb), which in turn provide a means to estimate variable crop water use within irrigated fields. However, monitoring spatial Kcb at sufficient temporal resolution using only aerial acquisitions would likely not be cost-effective for growers. In this study, we evaluated a model-based sampling approach, ESAP (ECe Sampling, Assessment, and Prediction), aimed at reducing the number of seasonal aerial images needed for reliable Kcb monitoring. Aerial imagery of NDVI was acquired over an experimental cotton field having two treatments of irrigation scheduling, three plant density levels, and two N levels. During both 2002 and 2003, ESAP software used input imagery of NDVI on three separate dates to select three ground sampling designs having 6, 12, and 20 sampling locations. On three subsequent dates during both the years, NDVI data obtained at the design locations were then used to predict the spatial distribution of NDVI for the entire field. Regression of predicted versus imagery observed NDVI resulted in r2 values from 0.48 to 0.75 over the six dates, where higher r2 values occurred for predictions made near full cotton cover than those made at partial cover. Prediction results for NDVI were generally similar for all three sample designs. Cumulative transpiration (Tr) for periods from 14 to 28 days was calculated for treatment plots using Kcb values estimated from NDVI. Estimated cumulative Tr using either observed NDVI from imagery or predicted NDVI from ESAP procedures compared favorably with measured cumulative Tr determined from soil water balance measurements for each treatment plot. Except during late season cotton senescence, errors in estimated cumulative Tr were between 3.0% and 7.3% using observed NDVI, whereas they were they were between 3.4% and 8.8% using ESAP-predicted NDVI with the 12 sample design. Thus, employing a few seasonal aerial acquisitions made in conjunction with NDVI measurements at 20 or less ground locations optimally determined using ESAP, could provide a cost-effective method for reliably estimating the spatial distribution of crop water use, thereby improving cotton irrigation scheduling and management.
• El-Shikha, D. M., Barnes, E. M., Clarke, T. R., Hunsaker, D. J., Haberland, J. A., Pinter, P. J., Waller, P. M., & Thompson, T. L. (2008). Remote sensing of cotton nitrogen status using the Canopy Chlorophyll Content Index (CCCI). Transactions of the ASABE, 51(Issue 1).
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  Various remote sensing indices have been used to infer crop nitrogen (N) status for field-scale nutrient management. However, such indices may indicate erroneous N status if there is a decrease in crop canopy density influenced by other factors, such as water stress. The Canopy Chlorophyll Content Index (CCCI) is a two-dimensional remote sensing index that has been proposed for inferring cotton N status. The CCCI uses reflectances in the near-infrared (NIR) and red spectral regions to account for seasonal changes in canopy density, while reflectances in the NIR and far-red regions are used to detect relative changes in canopy chlorophyll, a surrogate for N content. The primary objective of this study was to evaluate the CCCI and several other remote sensing indices for detecting the N status for cotton during the growing season. A secondary objective was to evaluate the ability of the indices to appropriately detect N in the presence of variable water status. Remote sensing data were collected during the 1998 (day of year [DOY] 114 to 310) and 1999 (DOY 106 to 316) cotton seasons in Arizona, in which treatments of optimal and low levels of N and water were imposed. In the 1998 season, water treatments were not imposed until late in the season (DOY 261), well after full cover. Following an early season N application in 1998 for the optimal (DOY 154) but not the low N treatment, the CCCI detected significant differences in crop N status between the N treatments starting on DOY 173, when canopy cover was about 30%. A common vegetation index, the ratio of NIR to red (RVI), also detected significant separation between N treatments, but RVI detection occurred 16 days after the CCCI response. After an equal amount of N was applied to both optimal and low N treatments on DOY 190 in 1998, the CCCI indicated comparable N status for the N treatments on DOY 198, a trend not detected by RVI. In the 1999 season, both N and water treatments were imposed early and frequently during the season. The N status was poorly described by both the CCCI and RVI under partial canopy conditions when water status differed among treatments. However, once full canopy was obtained in 1999, the CCCI provided reliable N status information regardless of water status. At full cotton cover, the CCCI was significantly correlated with measured parameters of N status, including petiole NO 3-N (r = 0.74), SPAD chlorophyll (r = 0.65), and total leaf N contents (r = 0.86). For well-watered cotton, the CCCI shows promise as a useful indicator of cotton N status after the canopy reaches about 30% cover. However, further study is needed to develop the CCCI as a robust N detection tool independent of water stress.
• El-Shikha, D. M., Waller, P., Hunsaker, D., Clarke, T., & Barnes, E. (2007). Ground-based remote sensing for assessing water and nitrogen status of broccoli. Agricultural Water Management, 92(Issue 3). doi:10.1016/j.agwat.2007.05.020
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  Remote sensing (RS) can facilitate the management of water and nutrients in irrigated cropping systems. Our objective for this study was to evaluate the ability of several RS indices to discriminate between limited water and limited nitrogen induced stress for broccoli. The Agricultural Irrigation Imaging System (AgIIS) was used over a 1-ha broccoli field in central Arizona to measure green (550 nm), red (670 nm), far red (720 nm), and near infrared (NIR-790 nm) reflectances, and thermal infrared radiation. Measurements were taken at a 1 m × 1 m resolution, every several days during the season. The following indices were calculated: ratio vegetation index (RVI), normalized difference vegetation index (NDVI), normalized difference based on NIR and green reflectance (NDNG), canopy chlorophyll concentration index (CCCI), and the water deficit index (WDI). The experimental design was a two-factor, nitrogen × water, Latin square with four treatments (optimal and low water and optimal and low nitrogen) and four replicates. In addition to RS measurements, the following in-situ measurements were taken: SPAD chlorophyll (closely related to nitrogen status), plant petiole nitrate-nitrogen concentrations, soil water content, and plant height, width, and leaf area index (LAI). Fresh marketable broccoli yield was harvested from plots 130 days after planting. Seasonal water application (irrigation plus rainfall) was 14% greater for optimal than low water treatments, whereas total nitrogen application was 35% greater for optimal than low N treatments. Although both nitrogen and water treatments affected broccoli growth and yield, nitrogen effects were much more pronounced. Compared to the optimal water and nitrogen treatment, broccoli yield was 20% lower for low water but optimal nitrogen, whereas yield was 42% lower for optimal water but low nitrogen. The RVI, NDVI, and NDNG indices detected treatment induced growth retardation but were unable to distinguish between the water and nitrogen effects. The CCCI, which was developed as an index to infer differences in nitrogen status, was found to be highly sensitive to nitrogen, but insensitive to water stress. The WDI provided appropriate information on treatment water status regardless of canopy cover conditions and effectively detected differences in water status following several irrigation events when water was withheld from low but not optimal water treatments. Using a RS ground-based monitoring system to simultaneously measure vegetation, nitrogen, and water stress indices at high spatial and temporal resolution could provide a successful management tool for differentiating between the effects of nitrogen and water stress in broccoli. © 2007 Elsevier B.V. All rights reserved.

Proceedings Publications

• Elshikha, D. E., Attalah, S., Waller, P., Hunsaker, D., Thorp, K. R., Williams, C., Sanyal, D., Singh, B., Sanchez, C., Norton, R., Alshraah, S., Barnes, E., Orr, E., & Elsadek, E. A. (2025). Enhancing Cantaloupe and Broccoli Water Productivity Under Arid Climate Conditions in Arizona. In 2025 American Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2025.
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  The present study was conducted to evaluate the effect of three irrigation methods: flood (F), subsurface drip (D), and center pivot (CP) on yield (Y) and water productivity (WP). Each irrigation method was tested at two application rates, 100% and 80% of crop evapotranspiration (ETc), denoted as “100” and “80”, respectively, under both amended (denoted as “a”) and non-amended soil conditions. Treatments were arranged in a randomized complete block design (RCBD) with three replicates during the 2024-2025 cantaloupe and broccoli growing seasons in Arizona, USA. Our results illustrated that the flood irrigation system achieved the highest cantaloupe yield (65.7 t ha-1 under F80a treatment). In contrast, the lowest cantaloupe yields (25.6 t ha-1 and 26.7 t ha-1) were achieved under CP80 and D80a treatments, respectively. Application of soil amendment, Liquid Natural Clay (LNC), resulted in slight to moderate increases in cantaloupe yields under flood irrigation and center pivot irrigation systems (1.3%-15.1%). However, under D80a treatment, cantaloupe yield declined by 2.4% compared to the non-amended D80 treatment, indicating a minimal or adverse response under the reduced irrigation rate. For broccoli, LNC improved yield for most treatments, with increases ranging from 5.8% to 13.6%, except under F80a where yield declined by 7.1%. Notable gain was observed under F100a (6.7%), D100a (9.6%) and CP100a (11.1%) treatments, compared to the corresponding non-amended treatments (F100, D100 and CP100). At the reduced (80%) irrigation rate, yield improvements were also evident under D80a (5.8%) and CP80a (13.6%). This highlights the potential of combining good irrigation strategies with soil amendments to improve crop yield. Our results indicated that within the scope of this study, the subsurface drip irrigation system showed the highest water productivity under deficit irrigation conditions, applying 80% of calculated ETc, both with and without soil amendment (6.25 kg m−3 and 6.62 kg m−3 for broccoli under the D80a and D80, respectively), followed by the center pivot and flood.
• Attalah, S., Elsadek, E., Waller, P., Hunsaker, D., Thorp, K., Bautista, E., Williams, C., Wall, G., Orr, E., & Elshikha, D. (2024, July 2024). Evaluating the Performance of OpenET Models for Alfalfa in Arizona. In ASABE Conference.
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  This study was conducted to evaluate six satellite-based ET models (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, and SSEBop) and their Ensemble, derived from the OpenET platform, in estimating the actual evapotranspiration (ET) of alfalfa. Then, identify the best-performing OpenET model for alfalfa irrigation management under arid climate conditions in Arizona, USA. Five statistical metrics, the index of agreement (Dindex), Nash-Sutcliffe efficiency coefficient (NSE), mean bias simulation error (MBE), prediction/simulation error (Pe), and coefficient of determination (R2), were used to evaluate the seven alternative estimates in comparison with measured ET (ETmea) at a field scale with four replicates during the 2023 alfalfa growing season in Buckeye, Arizona. Overall, OpenET models and their Ensemble were linearly correlated to average ETmea with R2 > 0.71. Our findings showed that ALEXI/DisALEXI, geeSEBAL, and PT-JPL had a general tendency to underestimate actual ET with acceptable to poor prediction errors (Pe ≤ -35.18 for PT-JPL). In contrast, eeMETRIC, SIMS, and SSEBop overestimated ETmea with acceptable to poor prediction errors (1.86 ≤ Pe ≤ 28.39). Our results highlighted the limitations of using the PT model in arid to semi-arid areas, even after the PT-JPL aridity correction. The Ensemble approach, which combined all OpenET models, showed a high degree of agreement (0.93 ≤ Dindex ≤ 0.96) with the ETmea of alfalfa during the growing period in 2023. R2 ranged from 0.77 to 0.86, with positive NSE values between 0.67 and 0.82. Moreover, the Ensemble approach had significantly lower prediction errors (-6.92 ≤ Pe ≤ 4.04) when compared with six OpenET models, making it the best to simulate alfalfa’s actual evapotranspiration over the study area. This will contribute to providing farmers and decision-makers with the best satellite-based approach for efficient irrigation management and water use in arid regions.
• Elshikha, D., Attalah, S., Elsadek, E., Waller, P., Thorp, K., Sanyal, D., Bautista, E., Norton, R., Hunsaker, D., Williams, C., Wall, G., Barnes, E., & Orr, E. (2024, July). The Impact of Gravity Drip and Flood Irrigation on Development, Water Productivity, and Fiber Yield of Cotton in Semi-Arid Conditions of Arizona. In Aly.
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  The present study was conducted to examine the effects of two irrigation methods with different application rates on cotton (ST 4595B3XF variety) growth, irrigation water productivity, and fiber yield in Arizona. Five treatments, namely gravity drip (GD) with 100%, 80%, and 60% of crop evapotranspiration (ETc) and flood (F) with 100% and 80% of ETc (GD 100%, GD 80%, GD 60%, F100%, and F80%, respectively), were arranged in a randomized complete block design (RCBD) with three replicates during 2023. Deficit irrigation (DI) reduced cotton height and canopy cover with both GD and F irrigations. Compared with the F system, the enhanced vegetative growth resulted in a notable increase in total irrigation requirements, particularly evident in the GD 100% (1337.50 mm) and GD 80% (1106.60 mm). The highest fiber yield values of 1621 kg ha−1 and 1465 kg ha−1 were recorded under an irrigation rate of 100% ETc for both GD and F irrigation. However, decreasing irrigation rates to 80% and 60% ETc negatively affected fiber yield under the two irrigation systems. Improvement of irrigation water productivity (WPI), accompanied by saving irrigation water and a high fiber yield, could be obtained by shifting irrigation from the GD 100% (I = 1337.50 mm, WPI = 0.121 kg m−3) and F100% rates (I = 1162.00 mm, WPI = 0.125 kg m−3) toward the GD 80% rate (I =1106.60 mm, WPI = 0.130 kg m−3). The lowest micronaire (MIC) values were recorded under F 80 % and F 100% (4.36 and 4.97, respectively). The 100% treatment of F and GD showed higher fiber strength (STR) (29.51 and 28.29 HVI g tex−1, respectively). However, the upper half mean length (UHML), uniformity index (UI), and short fiber content (SFC) values showed a downward trend under both GD and F treatments, reflecting their correlation with the total applied water. Elongation at failure (ELO) was consistent among irrigation treatments. This study provides significant guidance for adopting DI strategies in cotton under semi-arid conditions.
• Elshikha, D. E., Attalah, S., Waller, P., Hunsaker, D. J., Thorp, K. R., Williams, C., Katterman, M., Sanyal, D., Wang, G., Dierig, D., & Ray, D. (2023).

  Guayule Germination and Growth under Subsurface Gravity Drip and Furrow Irrigation in Arizona

  . In ASABE.
• Elshikha, D. E., Elshikha, D. E., Attalah, S., Attalah, S., Waller, P., Waller, P., Hunsaker, D. J., Hunsaker, D. J., Thorp, K. R., Thorp, K. R., Williams, C. F., Williams, C. F., Katterman, M. E., Katterman, M. E., Sanyal, D., Sanyal, D., Wang, G., Wang, G., Dierig, D. A., , Dierig, D. A., et al. (2023, July 2023). Guayule Germination and Growth under Subsurface Gravity Drip and Furrow Irrigation in Arizona. In ASABE Conference.
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  Guayule (Parthenium argentatum, A. Gray) is a perennial shrub, native to the desert of northcentral Mexico and southwestern Texas, which produces high quality natural rubber. The annual water requirement under flood irrigation is approximately 732 mm (2.4 acre-ft/year), which is within the annual water allocation depth for many central Arizona farmers. However, under the uncertainty of water supply in some areas, growers might be forced to cut irrigations or adjust their cropping practices. When flood irrigation is used, guayule germination requires about 380 mm of water, which can be reduced when a more efficient irrigation system is adopted. The objective of this study was to compare guayule germination and growth, as well as yield and water productivity under furrow irrigation (FI) and subsurface gravity drip (SGD) irrigation. A direct field-seeded guayule irrigation study was initiated in May 2022 on a 1.5-ha field at the University of Arizona, Maricopa Agricultural Center farm, in Maricopa, Arizona. The field study consisted of six plots: three 100 m x 18.3 m plots were under SGD and three 100 m x, respectively) 8.1 m plots were under FI. The experiment included one flood and one SGD treatments (denoted as F2.5 and D2.5, respectively), which were supposed to receive a predetermined irrigation amount (IA) of 762 mm (2.5 acre-ft/year) but they received 803 mm and 713 mm, respectively. Two other SGD treatments were included in the experiment, denoted as D2.0 and D1.5, which received IA of 615 mm (2.0 acre-ft/year) and 517 mm (1.7 acre-ft/year), respectively. Results indicated that SGD reduced water use during germination by 38%, with IA of 223 mm compared to 360 mm applied under FI, while providing a good crop stand with a slight increase in density (10 plants m-2) compared to FI (8 plants m-2). Moreover, SGD improved guayule yield and water productivity with D2.0 treatment being the best in terms of WP-DBY (1.56 kg m-3), followed by D2.5 (1.25 kg m-3), then D1.5 (1.13 kg/m3). There was no difference in WP-RY among SGD treatments (~0,04 kg m-3) nor in WP-ReY between D2.5 and D1.5 (0.09 kg m-3). The average for the three furrow plots was the lowest (WP-DBY = 0.83 kg m-3, WP-RY = 0.02 kg m-3, WP-ReY = 0.06 kg m-3) despite receiving the highest total irrigation amount [TWA] (941 mm). Rubber content (R, %) and resin content (Re, %) were slightly higher for D2.0 and D1.5 which received less water. Overall, using D2.0 treatment with 615 mm IA could save 20% of water while providing 37% more DBY, 21% more RY, and 47% more ReY than FI, which received 941 mm of water (irrigation + precipitation). (Download PDF)    (Export to EndNotes) ShareFacebookXEmail  
• Ray, D. T., Ray, D. T., Dierig, D., Dierig, D., Wang, G., Wang, G., Sanyal, D., Sanyal, D., Katterman, M. E., Katterman, M. E., Williams, C., Williams, C., Thorp, K. R., Thorp, K. R., Hunsaker, D. J., Hunsaker, D. J., Waller, P. M., Waller, P. M., Attalah, S., , Attalah, S., et al. (2023, Spring).

  Guayule germination and growth under subsurface gravity drip and furrow irrigation in Arizona

  . In 2023 ASABE Annual International Meeting, Paper number 2300034, 19.
• Andrade-Sanchez, P., Elshikha, D. E., & Thorp, K. R. (2021). Irrigation Management Outcomes using Increasingly Complex Geospatial Technologies. In 6th Decennial National Irrigation Symposium, 6-8, December 2021, San Diego, California.
• Waller, P., Katterman, M. E., Bronson, K. F., Cruz, M. V., Wang, S., Dierig, D. A., Hunsaker, D. J., & Elshikha, D. E. (2019). Direct seeded guayule grown in Arizona under furrow and subsurface drip irrigation. In ASABE annual international meeting.
• Bronson, K. F., Elshikha, D. E., & Hunsaker, D. F. (2017). Response of guayule biomass and rubber yield to variable water inputs using subsurface drip irrigation. In 2017 ASABE annual international meeting, Spokane, Washington July 16 - July 19, 2017.
• Hunsaker, D., & Elshikha, D. E. (2016). Guayule biomass and rubber yield under variable water inputs using surface irrigation. In 2016 ASABE Annual International Meeting.
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  Interest in agricultural production of guayule (Parthenium argentatum G.) in Southwestern USA deserts is spurred by a goal of attaining a domestic natural rubber supply. Limited and dated information on guayule irrigation management exists but advanced knowledge is needed for today's growers. In this paper, guayule growth, rubber, yield, and crop evapotranspiration (ETc) responses to irrigation were evaluated for a present-day cultivar, Yulex-B, during a 29-month surface irrigation study in Maricopa, Arizona USA. Seedlings were transplanted within a 1.4-ha field in October 2012, at 0.36-m spacing, along 1.02-m by 100-m rows. Five irrigation treatments were imposed in three block replicates from April 2013 through 2015, prior to final harvest in March 2015. Treatment irrigation amounts were 40, 60, 80, 100, and 120% of irrigation applied to the 100% treatment, based on measured soil water depletion (SWD) for the 100%. Measured SWD percentage prior to irrigation for the 100% averaged 59%. The total water applied (TWA), including rain, from transplanting to final harvest, varied from 2370 to 4720 mm. Cumulative ETc measured from April 2013 through March 2015 varied from 1750 to 3660 mm. At final harvest, dry biomass (DB) varied from 15, 700 to 27, 900 kg/ha and rubber yield (RY) from 1220 to 1680 kg/ha. The study confirms that both DB and RY respond linearly to irrigation input, thus, maximizing DB maximizes rubber yield. For maximum rubber yield using surface irrigation, it is recommended to use SWD of 50% for irrigation scheduling and apply ≈1950 mm/year of total water. However, guayule water productivity (yield per unit TWA) can be significantly increased by reducing TWA by 25% (i.e., 1460 mm/year). This application achieved 92% of the maximum RY in the study.
• Sanchez, P., Bronson, K. F., Hunsaker, D. J., & Elshikha, D. E. (2016). Using RGB-based vegetation indices for monitoring guayule biomass, moisture content and rubber. In 2016 ASABE annual international meeting.
• Elshikha, D. E., & Hunsaker, D. J. (2014). Yield and water use of guayule grown in Arizona. In 2014 ASABE annual international meeting.
• Hunsaker, D. J., & Elshikha, D. M. (2014). Using a simplified surface energy balance procedure and a stochastic calibration modeling procedure to predict the spatial distribution of cotton evapotranspiration. In American Society of Agricultural and Biological Engineers Annual International Meeting 2014, ASABE 2014, 2.
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  Fraction of plant evapotranspiration (ETf) can be estimated reasonably well using surface energy balance models. Recent studies have estimated ETf using models such as Surface Energy Balance Algorithms for Land (SEBAL) and Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC) with satisfactory results for local and regional scales. However, due to the need for high quality data along with personnel skilled and knowledgeable in energy balance modeling, a simpler energy balance procedure known as the simplified surface energy balance equation (SSEB) was introduced in 2007. In this study, a model-based sampling and prediction approach, ESAP (ECe Sampling, Assessment, and Prediction), was used. The evaluation data was collected during a cotton experiment conducted for two years (2002 and 2003) on a 1.3 ha field at The University of Arizona, Maricopa Agricultural Center in Maricopa Arizona. The experiment consisted of 32 plots (each 11.2 m by 21 m) assigned to twelve different sub-treatments. The main treatment consisted of two basal crop coefficient (Kcb) estimation methods: 1) Kcb estimated following the FAO-56 procedures [the FAO (F) treatment], and 2) Kcb estimated using observations of the normalized difference vegetation index (NDVI) [the (N) treatment]. Each Kcb treatment had 16 plots. The sub-treatments consisted of three plant densities (dense, typical and sparse) and two nitrogen fertilization levels (high and low). The main and sub-treatments were imposed to create differences in cotton growth and water use responses among plots. For the SSEB procedure, measured surface temperature was first plotted versus observed NDVI to form a trapezoid. From the trapezoid, the high (THot) and low (TCou) temperature lines were defined by calculating an equation for each line. The equations are used in the procedure to determine the upper (THot) and lower (TCold) limits for each data point given its NDVI value. For a plot with a given temperature, T, ETf was calculated by dividing (THot-T) by (THot-TCold)- ETfwas adjusted with NDVI to account for the differences in transpiration rate due to different canopy densities. Then, the estimated ETf data was imported to ESAP software to determine the best sampling locations and to predict the spatial distribution of ET. Results indicate good correlation between the calculated ET values and measured soil moisture contents. Also, results indicated reasonable correlation between the calculated and measured ET with the calculated explaining 60% of the variability in the experimental field. Statistical tests indicated good correlation between the measured and predicted ET using the ESAP stochastic calibration procedure (spatial regression modeling).
• El Shikha, M. A., El-Kiran, M., El Shikha, D. M., & Salam, M. S. (2009). Reactive maintenance of hydraulic cylinders in agricultural equipments. In American Society of Agricultural and Biological Engineers Annual International Meeting 2009, 3.
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  A hydraulic system is one of the most important engineering applications used in agricultural machines. The hydraulic cylinders, used in most of these agricultural equipments, are responsible for the conversion of hydraulic energy to frequent mechanical movement. The majority of the hydraulic equipment stops, during work, are due to malfunction of the hydraulic cylinders, namely, due to the fluid leakage. The leakage is mainly internally (from the piston seals) and sometimes externally (from rod seals). Therefore, this study aims to investigate the major causes of the hydraulic cylinder failure (i.e. due to seal damage) that may result in forced stop of the equipments; and to determine the best way to maintain and reconstruct the cylinders. Cylinder maintenance treatments considered in this study included: (1) cylinder surface finishing treatments [turnings only, polishing (after turning), and electroplating (after polishing)] of the cylinder internal surface using chrome (known to increase corrosion resistance); (2) Piston diameter (without, with one and two pressure rings); and (3) Hydraulic fluid viscosity (three different viscosities). The force needed to move the pistons on the treated cylinder surface was measured. Results indicated that the best performance was obtained from the cylinder that had its internal surface chromium electroplated (the force needed was at least 50% less than the other treatments). In addition, chromium electroplating minimized the chemical reaction between the cylinder surface and the hydraulic fluids.
• El-Shikha, D. M., Hunsaker, D. J., French, A., Waller, P., & Clarke, T. (2009). Sensitivity of canopy chlorophyll concentration index (CCCI) for water stress. In American Society of Agricultural and Biological Engineers Annual International Meeting 2009, 3.
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  A variety of remote sensing indices have been used to infer crop nitrogen (N) status for field-scale nutrient management. However, such indices may indicate incorrect N status if there is a decrease in crop canopy density influenced by other growth retardation factors, such as water stress. The Canopy Chlorophyll Content Index (CCCI) is a two-dimensional remote sensing index that has been proposed for inferring cotton N status. The CCCI uses reflectances in the near-infrared (NIR) and red spectral regions to account for seasonal changes in canopy density, while reflectances in the NIR and far-red regions are used to detect relative changes in canopy chlorophyll, a surrogate for N content. The primary objective of this study was to evaluate the CCCI for detecting the N status for cotton, broccoli and wheat during the growing season without being affected by water stress. Remote sensing data were collected during cotton (1998 and 1999), broccoli (2001), and wheat (2004 and 2005) experiments. Experiments included treatments of optimal and low levels of N and water. They were carried out at The University of Arizona's Maricopa Agricultural Center (MAC) located approximately 40 km south of Phoenix, AZ, USA. The primary results indicated that the CCCI is significantly correlated with the measured parameters of nitrogen status, including petiole NO3-N, SPAD chlorophyll, and leaf total nitrogen. The CCCI was found to be highly sensitive to nitrogen, but mostly insensitive to water stress, especially at full cover. The CCCI can be used as a successful management tool for differentiating between the effects of nitrogen and water stress in wheat. However, CCCI was not very reliable with wheat or broccoli at times of severe water stress.
• El-Shikha, M. A., Abd-Elmageed, H. N., Mostafa, M. A., El-Shikha, D. M., & El-Kolally, W. F. (2009). A human driven power unit developed for agricultural uses. In American Society of Agricultural and Biological Engineers Annual International Meeting 2009, 3.
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  Small farms (less than 0.5 hectare) are very common in Egypt and many developing countries, which typically have vast growing populations with limited job opportunities. Using human resources in such conditions is mandatory. Therefore, this investigation was carried out to develop a human powered unit (prone cart-driven by two men) suitable for small farms. Four men were considered to drive the unit alternatively. This power unit was tested on two surfaces (paved and unpaved roads). The experiments included the following treatments: (1) pedal to drive wheel reduction ratio (1:2.5, 1:3.5 and 1:4.5), (2) traction mass [(25, 50 and 75 kg) on unpaved roads and (75, 100 and 125 kg) on paved road], (3) drawbar height (30, 35 and 40 cm), (4) tire inflation pressure (1.0, 1.5 and 2.0 bars). To evaluate the performance of the designed unit, the forward speed, slippage, rolling resistance were estimated. Results indicated that the best forward speed and drawbar pull of the unit were 2.56 km/hr and 55 kg, respectively, and the resulting slippage was 1.14 % on the paved road. However on the unpaved road, the best forward speed, drawbar pull, and slippage were 1.84 km/hr, 60 kg, and 3.26 %, respectively. Results show promises of using the human powered unit to do light farm operations such as applying fertilizers, weed and pesticide spraying and flame weed control. Future research is needed to test the ability of the developed unit to do different farm operations.
• El-Shikha, D. M., Hunsaker, D. J., Lesch, S. M., Clarke, T. R., French, A. N., & Thorp, K. (2008). Determining fixed sensor locations for predicting the spatial distribution of ndvi using esap software. In American Society of Agricultural and Biological Engineers Annual International Meeting 2008, 2.
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  A software package called ESAP (a salinity modeling software package) was used for designing the optimal sampling i.e., fixed sensors locations to estimate the spatial distribution of NDVI in a cotton field. Then it was used to estimate calibration equations and generate maps of the predicted and observed NDVI for the entire field. The ESAP software package consists of three programs: ESAP-RSSD, ESAP-Calibrate and ESAP-Mapping. The ESAP-RSSD was used to generate optimal sampling designs for NDVI spatial distribution estimation. The ESAP-Calibrate was used to estimate calibration equations (i.e. model parameter estimation). The ESAP-Mapper was designed to generate maps of survey and predicted data to compare predicted and observed NDVI data. Model estimation was based on 20 sampling locations. The main objective was to study the ability of the ESAP software to cost-efficiently estimate the spatial distribution of NDVI in a cotton field (i.e., obtaining a small number of sampling locations, consequently a small number of sensors needed to describe the field distribution of NDVI). The field NDVI spatial distribution was predicted for three different dates during the season using DOY163 as a survey to predict DOY176 (called group 1), using DOY226 as a survey to predict DOY246 (group 2) and using DOY246 as a survey to predict DOY261 (group 3). Regression of predicted versus observed NDVI data based on the ESAP sampling sites resulted in R-square values of 0.56, 0.51 and 0.81 for the three profile dates, respectively. These R2 values and the associated MSE estimates (0.089, 0.079 and 0.045) compared well to the observed R2 and MSE estimates based on the entire set of NDVI sample data (over 17,000 pixels). The results indicate that the ESAP model can be a reliable tool for locating a relatively small number of fixed sensors, whose combined NDVI data would allow a good prediction of the spatial distribution of NDVI for an entire field.
• El-Shikha, M. A., El-Berry, A., El-Shikha, D. M., & Zayed, M. (2008). A laser scraper modification and its effect on performance and operational costs. In American Society of Agricultural and Biological Engineers Annual International Meeting 2008, 2.
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  A field experiment was carried out during the agricultural season of 2004 on a clay soil to evaluate the performance of a modified laser scraper compared to an unmodified scraper. The modification consisted of adding 8 chisel shanks on the main frame of the scraper set at equal distances along the width of the scraper. The objective of the modification is to eliminate firm, un-chiseled, spots that normally appear during leveling with the unmodified laser scraper. In such cases, a chisel plow has to be used to loosen the soil in-between scraper runs to level these spots, which increases the operational costs. Leveling was performed at two slopes; 0% and 0.03%. Results indicate that leveling at 0% slope with the modified laser scraper results in a more homogeneous land surface with no firm, un-chiseled, spots than with the conventional scraper. Comparison of the unmodified laser scraper at the two slopes produced more homogenous leveling at the 0.03% slope. Leveling with the modified scraper at the 0.03% slope resulted in two small areas with higher level than the surrounding ground, which indicates the need for a chisel shank that can go deeper in the soil (more than the 4 cm below cutting blade). The modified laser scraper resulted in better soil physical properties such as higher porosity and lower soil bulk density. Also, it resulted in better soil pulverization at both slopes (0% and 0.03%). Although the modified laser scraper required more power, operational costs decreased by about 32% in comparison with the unmodified scraper for both slopes. In summary, using the modified laser scraper gave more precise leveling at lower cost. Increasing the depth of the chisel shanks helps reduce the chance of leaving firm, un-chiseled soil.

Others

• Elshikha, D. M., Waller, P., Masson, R., & Subramani, J. (2023, March). Guayule Cultivation and Irrigation Methods for the Southwestern United States.
• Elshikha, D. M., Waller, P., Thorp, K., Angadi, S., Grover, K., & Masson, R. (2023, February). Using Drones for Management of Crops.