Guidance for Soil Moisture Sensor Selection: Market Analysis and Decision-Making Strategies

Monitoring soil moisture content is a critical aspect of effective irrigation scheduling. Maintaining optimal soil moisture levels is essential for plant growth and crop yield. Soil moisture monitoring can be accomplished through various methods, including the use of capacitance sensors that measure dielectric properties for volumetric water content assessments. Alternatively, traditional methods such as gravimetric sampling, primarily utilized in research, require weighing soil samples before and after drying to determine moisture content. These methods provide valuable insights for irrigation management, helping growers optimize water use and enhance crop productivity (Gu et al., 2020)

Using Drones for Management of Crops

A wide range of circumstances adversely affect crop growth and plant health. Crops are susceptible to disease (insects, fungus, etc.), improper levels of nutrients in the soil and availability of water, all of which impact a plant’s growth and yield

Guayule Cultivation and Irrigation Methods for the Southwestern United States

As water becomes scarce in Arizona there is a desire by growers to grow crops that use less water. With hundreds of acres already planted across the state and the plan to scale to 10,000 acres over the course of three years, guayule has become a more water wise crop than traditional desert row crops like silage corn, alfalfa, and cotton. In this guide, cultivation and irrigation methods will be discussed to increase area under guayule across the state

Managing ratooned guayule in the Southwestern United States

In Arizona, sufficient water supply for agriculture has become a growing concern for farmers due to drought and the depletion of groundwater supply. Therefore, crops like guayule that provide economic value while consuming less water will be needed. Since guayule follows a perennial lifecycle, it can be cut and regrown multiple times after the initial harvest with a process called ratooning. In general, ratooned guayule requires less water than replanting as more water is needed at crop establishment to support seedlings than is needed to regrow mature plants. This can result in lower irrigation costs if an optimized irrigation regime is adopted. The following guide leverages data from several years of Arizona grown guayule and provides a specialized irrigation strategy in terms of irrigation amounts and timing to save water and optimize growth for ratooned guayule

Impacts of Deficit Irrigation on Barley and Durum Wheat Production in Arizona: A Preliminary Report

Deficit irrigation is often considered an effective irrigation strategy to conserve water and has been tested in different crop production systems and under different environments. In this research study, we explored the impact of deficit irrigation in the arid Southwest region, particularly in central Arizona, on the production of durum wheat and grain barley using flood irrigation. The experiment was conducted at the University of Arizona Maricopa Agricultural Center in Maricopa, Arizona. We examined irrigation deficits of 12.5% and 25% and observed that a 12.5% deficit in irrigation led to 30% and 45% decline in grain yield for durum wheat and barley, respectively; however, the yield did not decline further under the 25% deficit irrigation treatment. Additionally, we did not record any changes in soil chemical properties or soil health. Our study concluded that under flood-irrigated durum wheat and barley, deficit irrigation may not be an economically viable strategy for water conservation in desert agroecosystems. However, this research also highlighted the need for similar research on drip- and sprinkler-irrigated small grain production systems

WINDS Model Demonstration with Field Data from a Furrow-Irrigated Cotton Experiment

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

WINDS Model Simulation of Guayule Irrigation

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

Transcriptomic and evolutionary analysis of the mechanisms by which P. argentatum, a rubber producing perennial, responds to drought

Background Guayule (Parthenium argentatum Gray) is a drought tolerant, rubber producing perennial shrub native to northern Mexico and the US Southwest. Hevea brasiliensis, currently the world's only source of natural rubber, is grown as a monoculture, leaving it vulnerable to both biotic and abiotic stressors. Isolation of rubber from guayule occurs by mechanical harvesting of the entire plant. It has been reported that environmental conditions leading up to harvest have a profound impact on rubber yield. The link between rubber biosynthesis and drought, a common environmental condition in guayule's native habitat, is currently unclear. Results We took a transcriptomic and comparative genomic approach to determine how drought impacts rubber biosynthesis in guayule. We compared transcriptional profiles of stem tissue, the location of guayule rubber biosynthesis, collected from field-grown plants subjected to water-deficit (drought) and well-watered (control) conditions. Plants subjected to the imposed drought conditions displayed an increase in production of transcripts associated with defense responses and water homeostasis, and a decrease in transcripts associated with rubber biosynthesis. An evolutionary and comparative analysis of stress-response transcripts suggests that more anciently duplicated transcripts shared among the Asteraceae, rather than recently derived duplicates, are contributing to the drought response observed in guayule. In addition, we identified several deeply conserved long non-coding RNAs (lncRNAs) containing microRNA binding motifs. One lncRNA in particular, with origins at the base of Asteraceae, may be regulating the vegetative to reproductive transition observed in water-stressed guayule by acting as a miRNA sponge for miR166. Conclusions These data represent the first genomic analyses of how guayule responds to drought like conditions in agricultural production settings. We identified an inverse relationship between stress-responsive transcripts and those associated with precursor pathways to rubber biosynthesis suggesting a physiological trade-off between maintaining homeostasis and plant productivity. We also identify a number of regulators of abiotic responses, including transcription factors and lncRNAs, that are strong candidates for future projects aimed at modulating rubber biosynthesis under water-limiting conditions common to guayules' native production environment.USDA Biomass Research and Development Initiative (BRDI) [USDA-NIFA 201210006-19391 OH]; USDA-NIFA Coordinated Agricultural Program; Sustainable Bioeconomy for Arid Regions (SBAR) [2017-68005-26867]; National Science FoundationNational Science Foundation (NSF) [IOS-1758532]; University of Arizona; SBAROpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Growth, water use, and crop coefficients of direct-seeded guayule with furrow and subsurface drip irrigation in Arizona

Crop establishment costs of guayule (Parthenium argentatum A. Gray), a perennial desert shrub that produces natural rubber, can be significantly reduced using direct seeding rather than the traditional practice of transplanting greenhouse-grown seedlings. However, information regarding the irrigation application, crop evapotranspiration (ETc), and crop coefficients (Kc) for managing direct-seeded guayule crops has not been provided. In this study, guayule was direct-seeded in Apr. 2018 in fields at two location in Arizona; Maricopa, on a sandy loam soil and Eloy, on a clay soil, and harvested 23–24 months later in 2020. At each location, five irrigation rates were applied with subsurface drip irrigation (SDI) ranging from 50 to 150 % replacement of ETc (denoted as D50 to D150 treatments), respectively. A 6th treatment using furrow irrigation at 100 % ETc replacement (F100) was included. Treatments were replicated three times. The ETc was estimated for the first 74–84 days of crop establishment and thereafter, actual ETc (ETc act) was determined weekly-biweekly for the D100 and F100 treatments using a soil water balance. The objectives were to evaluate the responses in dry biomass (DB), rubber yield (RY), and resin (ReY) yield to water application rate, develop irrigation management criteria for the two soil types, and determine the ETc and crop coefficients for the 100 % treatments. The total irrigation applied to treatments ranged from 1830−1910 mm to 5090–5470 and averaged 3590 and 3320 mm for the 100 % SDI (D100) and furrow (F100) treatments at Maricopa and Eloy, respectively. The summed estimated ETc plus ETc act for the D100 and F100 treatments were 3663 and 3506 mm at Maricopa, respectively and 3428 and 3320 at Eloy, respectively. Average measured mid-season Kc in the 1st year varied from 1.20 to 1.26. Average measured mid-season Kc in the 2nd year were higher for D100 (≈1.30) than for F100 (≈1.23). Adjusted to the standard climate proposed in FAO56, mid-season Kc are 1.24 for D100 and 1.17 for F100 in the 2nd year. Average DB at Eloy (28.6 Mg ha−1) was not significantly higher than at Maricopa (24.0 Mg ha−1). However, RY and ReY were both significantly higher at Maricopa. At each location, rubber content was significantly higher for the F100 and the two lowest SDI rates than for other treatments. The highest mean RY and ReY were achieved with D100 at Maricopa and D75 at Eloy. These two also had significantly greater water productivity (WP; DB, RY, and ReY per unit of total water applied) than those at higher SDI rates and the F100 treatments. RY and ReY and their WP were generally higher for D100 than F100 in the sandy loam but not in the clay soil. For direct-seeded guayule in clay soils, furrow irrigation should be considered due to the lower rubber content and higher costs associated with SDI.24 month embargo; available online 14 July 2021This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Estimation of direct-seeded guayule cover, crop coefficient, and yield using UAS-based multispectral and RGB data

Guayule (Parthenium argentatum, A. Gray), a perennial desert shrub, produces high-quality natural rubber and is targeted as a domestic natural rubber source in the U.S. While commercialization efforts for guayule are on-going, crop management requires plant growth monitoring, irrigation requirement assessment, and final yield estimation. Such assistance for guayule management could be provided with remote sensing (RS) data. In this study, field and RS data, collected via drones, from a 2-year guayule irrigation experiment conducted at Maricopa, Arizona were evaluated. In-season field measurements included fractional canopy cover (fc), basal (Kcb) and single (Kc) crop coefficients, and final yields of dry biomass (DB), rubber (RY), and resin (ReY). The objectives of this paper were to compare vegetations indices from MS data (NDVI) and RGB data (triangular greenness index, TGI); and derive linear prediction models for estimating fc, Kcb, Kc, and yield as functions of the MS and RGB indices. The NDVI and TGI showed similar seasonal trends and were correlated at a coefficient of determination (r2) of 0.52 and a root mean square error (RMSE) of 0.11. The prediction of measured fc as a linear function of NDVI (r2 = 0.90) was better than by TGI (r2 = 0.50). In contrast to TGI, the measured fc was highly correlated with estimated fc based on RGB image evaluation (r2 = 0.96). Linear models of Kcb and Kc, developed over the two years of guayule growth, had similar r2 values vs NDVI (r2 = 0.46 and 0.41, respectively) and vs TGI (r2 = 0.48 and 0.40, respectively). Final DB, RY, and ReY were predicted by both NDVI (r2 = 0.75, 0.53, and 0.70, respectively) and TGI (r2 = 0.72, 0.48, and 0.65, respectively). The RS-based models enable estimation of irrigation requirements and yields in guayule production fields in the U.S.NIFA24 month embargo; available online: 11 February 2022This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]