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In the context of modern agriculture, efficient irrigation management plays a crucial role in optimizing tree growth and promoting sustainable management practices. This article introduces IrrigMonitor, an Internet of Things (IoT) data visualization platform developed at the UF Indian River Research and Education Center (IRREC) Smart Irrigation and Hydrology lab. IrrigMonitor is a centralized system that offers real-time insights into soil moisture levels and allows for customized adjustments based on specific soil conditions. This article presents an overview of IrrigMonitor's interface, explores its functionality, and discusses its potential applications in citrus water and nutrient management.

Accurate and near real-time volumetric soil water and volumetric ion content (VIC) measurements can both inform precise irrigation scheduling and aid in fertilizer management applications in cropping systems. To assist in the monitoring of these measurements, capacitance-based soil moisture probes are used in agricultural best management practice (BMP) programs. However, the ability of these sensors to detect nutrients in the soil sourced from fertilizers is not well understood. The objective of this study was to evaluate the sensitivity of a capacitance-based soil moisture probe in detecting Nitrogen (N), Phosphorous (P), and Potassium (K) movement in the soil. To achieve this, a laboratory-based setup was established using pure sand soil cores. Raw soil moisture and VIC probe readings from the cores were contrasted across multiple N, P, and K rates. The N treatments applied were rates of 0, 112, 168, and 224 kg/ha; for P, were 0, 3.76, and 37.6 kg/ha, and for K were 0, 1.02, 1.53, and 2.04 kg/ha. Each nutrient was evaluated separately using a randomized complete block design experiment with three replications for N and K, and 5 replications for P. The impact of each nutrient rate on the sensitivity of VIC readings was determined by evaluating differences in three points of the time series, including the observed maximum point, inflection point, and convergence value as well as the time of occurrence of those points over a 24-hour period. These points were assessed at depths 5, 15, 25, 35, 45, and 55 cm. The findings of this study highlight the capacitance-based soil moisture probes’ responsiveness to changes in all K rates at most depths. However, its sensitivity to changes in N and P rates is comparatively lower. The results obtained in this study can be used to develop fertilizer management protocols that utilize K movement as the baseline to indirectly assess N and P, while helping to inform those who currently use the probe which nutrients the probe may be detecting. The probes’ readings could be incorporated into decision support systems for irrigation and nutrient management and improve control systems for precision water and nutrient management.

Esta guía esta orientada para personal de extensión que pueda encontrar preguntas de los productores acerca del funcionamiento y precisión de sensores de humedad del suelo (SMSs) para producción de arboles frutales. La información en este documento permitirá a los especialistas de extensión responder algunas preguntas generales acerca de los SMSs. Esta publicación se enfoca en dos tipos de sensores portátiles usados actualmente en Florida para manejo de irrigación en cítricos y otros arboles: El oscilador de línea de transmisión (TLO) y el transmisometro en el dominio del tiempo (TDT) por sus siglas en ingles. Para detalles acerca de SMSs no descritos en esta publicación o alguna marca de SMS en particular, personal de extensión puede consultar los autores o un especialista de irrigación local.

IntroductionThe rhizosphere community composition has been shown to provide benefits in nutrient acquisition and plant health. Rhizosphere communities can be heavily influenced by cultural practices in citrus production systems, providing benefits in soil and root health, and plant physiology. Florida growers are implementing new and more sustainable soil management practices, such as using fabric mulch ground covers to improve weed and pest control, while retaining soil moisture. Little is known regarding the influence of these ground covers on the rhizosphere microbial communities of lemon trees, especially under endemic Huanglongbing pressure. Understanding how lemon roots and the rhizosphere microbiome are influenced by fabric mulch ground covers can potentially lead to improved management practices. The aim of this research was to evaluate the effects of fabric mulch ground covers on lemon tree rhizosphere health.MethodsThe experiment was conducted in a commercial citrus grove located in Fort Pierce, FL, US. Plant material consisted of four-year old lemon trees cv. ‘Meyer’ (Citrus limon) grafted on ‘sour orange’ (Citrus × aurantium) rootstocks. The experiment consisted of two treatments, which included trees grown with fabric mulch ground covers and trees grown without fabric mulch ground covers. Rhizosphere DNA was extracted, sequenced, and analyzed to assess differences in diversity and composition (alpha and beta diversity) of rhizosphere bacteria among treatments.Results and DiscussionObtained results showed that lemon trees treated with fabric mulch ground covers had significantly greater rhizosphere bacterial diversity when compared to the uncovered trees. The presence of fabric mulch ground covers resulted in significantly greater soil Zn, soil Mn, soil temperatures and pH, potentially contributing towards the significant more diverse rhizosphere bacterial commu nity composition compared than those grown without fabric mulch ground covers.

Managing one issue in the orchard might have an impact on other issues, and those impacts are not always bad. Landscape fabric groundcovers, for example, have been used for pest management in citrus production, and recently to promote the homogeneous availability of water for uptake by roots, better tree physiological development for new plantings, and even higher yields when the groundcovers are managed with proper irrigation scheduling methods such as soil-moisture sensor use. We present a 3rd-year update on the groundcover study for water management developed at a commercial field in Fort Pierce, FL and provide an overview of the opportunities and challenges when using groundcovers for pest management.

Huanglongbing (HLB) disease has caused a severe decline in citrus production globally over the past decade. There is a need for improved nutrient regimens to better manage the productivity of HLB-affected trees, as current guidelines are based on healthy trees. The aim of this study was to evaluate the effects of different fertilizer application methods and rates with different planting densities on HLB-affected citrus root and soil health. Plant material consisted of ‘Ray Ruby’ (Citrus × paradisi) grapefruit trees grafted on ‘Kuharske’ citrange (Citrus × sinensis × Citrus trifoliata). The study consisted of 4 foliar fertilizer treatments, which included 0×, 1.5×, 3× and 6× the University of Florida Institute of Food and Agriculture (UF/IFAS) recommended guidelines for B, Mn and Zn. Additionally, 2 ground-applied fertilizer treatments were used, specifically controlled-release fertilizer (CRF1): 12−3−14 + B, Fe, Mn and Zn micronutrients at 1× UF/IFAS recommendation, and (CRF2): 12−3−14 + 2× Mg + 3× B, Fe, Mn and Zn micronutrients, with micronutrients applied as sulfur-coated products. The planting densities implemented were low (300 trees ha−1), medium (440 trees ha−1) and high (975 trees ha−1). The CRF fertilizer resulted in greater soil nutrient concentrations through all of the time sampling points, with significant differences in soil Zn and Mn. Grapefruit treated with ground-applied CRF2 and 3× foliar fertilizers resulted in the greatest bacterial alpha and beta diversity in the rhizosphere. Significantly greater abundances of Rhizobiales and Vicinamibacterales were found in the grapefruit rhizosphere of trees treated with 0× UF/IFAS foliar fertilizer compared to higher doses of foliar fertilizers.

This guide is for Extension personnel who may encounter questions from growers about the functioning and accuracy of soil moisture sensors (SMSs) for fruit tree production. The 4-page publication focuses on two types of handheld sensors currently used in Florida for irrigation management of citrus and other trees: the transmission line oscillator (TLO) and time-domain transmissometer (TDT). Written by Eric Herrera, Sandra M. Guzmán, and Eduart Murcia, and published by the UF/IFAS Department of Agricultural and Biological Engineering, February 2021.

Understanding how to obtain and interpret the data coming from the soil moisture sensor (SMS) systems could be one of the most important parts of efficient irrigation management. These systems allow obtaining an efficient and informed irrigation scheduling plan based on soil moisture readings collected at the field. Below we answer some of the common questions when managing SMS systems including what is necessary to visualize SMS data in the computer, what kind of electronics allows data transfer from the field to the computer, and what is the best position to locate the sensors in the field. We also discuss CropMonitor a UF made software to visualize SMS data.

Understanding plants’ response to different irrigation levels is essential for developing effective irrigation scheduling practices that conserve water without affecting plant growth and yield. The objective of this study was to evaluate the responses of three sweet corn (Zea mays var. saccharata) cultivars 1170, 8021, and Battalion under three irrigation levels (50%, 75%, and 100%). Irrigation treatments were based on soil moisture management allowable depletion. Replicated trials were conducted, in an open field using 1-gal containers, at the Tropical Research and Education Center, Homestead, FL. A drip system with microsprinklers was used for irrigation. Daily crop evapotranspiration (ETc) rates were measured using a digital scale based on differences in weights of soil containers and plants. Reference evapotranspiration (ETo) was calculated using the FAO-Penman-Monteith equation. Crop-coefficient (Kc) values for the three cultivars were calculated from measured ETc and calculated ETo. In addition, leaf area, stomatal conductance, and fresh biomass were measured. Total irrigation amounts corresponding to the 50%, 75%, and 100% treatments were 116, 162, and 216 mm, and total ETc values were 128, 157, and 170 mm, respectively. The two deficit irrigation treatments (50% and 75%) resulted in a reduction of ETc for the three cultivars compared with the 100% irrigation treatments. Results also showed that under 75% and 100% treatments, Kc values were usually greater than 1 for the three cultivars and reached as high as 1.5. Additionally, leaf area and fresh biomass weight in the 50% treatment were mostly lower than in the 75% or 100% treatments.

This publication introduces water storage strategies known as Dispersed Water Management (DWM) and Water Farms (WF) and describes the process that a private landowner should follow to obtain a permit and begin a water storage agreement with the South Florida Water Management District (SFWMD) and the St. Johns River Water Management District (SJRWMD). Written by Brandon Quinn-Ivey and Sandra M. Guzmán, and published by the UF/IFAS Department of Agricultural and Biological Engineering, September 2022.

This publication discusses a few major consequences of improper irrigation design. Written by Haimanote K. Bayabil, Sandra M. Guzman, Fedro S. Zazueta, and Dorota Z. Haman, and published by the UF/IFAS Department of Agricultural and Biological Engineering, revised August 2022.

Part of a series on ET-based irrigation scheduling for agriculture, this article identifies typical Kc values for some of the crops commonly grown in Florida. Originally published January 2010 with minor update February 2013. This revision with Sandra M. Guzman, and Haimanote K. Bayabil AE456/AE456: Evapotranspiration-Based Irrigation for Agriculture: Crop Coefficients of Some Commercial Crops in Florida (ufl.edu)

This publication is part of a series on evapotranspiration (ET)-based irrigation scheduling in agriculture and outlines step-by-step procedures for implementing a “smart” ET-based irrigation schedule and a do-it-yourself irrigation schedule. Revised April 2019 with Haimanote K. Bayabil and Sandra M. Guzman.

Provides growers with an introduction to psychrometrics, which can be used as a tool to time the use of frost protection methods. Includes examples and charts. Update by Haimanote K. Bayabil and Sandra M. Guzman, May 2019.

AE457, a 6-page fact sheet by Isaya Kisekka, Kati W. Migliaccio, Michael D. Dukes, Jonathan H. Crane, and Bruce Schaffer, focuses on the main concepts related to ET-based irrigation scheduling and reviews the use of "smart" irrigation scheduling controllers for agricultural applications. Includes references. Updated May 2019 by Haimanote K. Bayabil and Sandra M. Guzman.

Global climate change is presenting a variety of challenges to hydrology and water resources because it strongly affects the hydrologic cycle, runoff, and water supply and demand. In this study, we assessed the effects of climate change scenarios on hydrological variables (i.e., evapotranspiration and runoff) by linking the outputs from the global climate model (GCM) with the Soil and Water Assessment Tool (SWAT) for a case study in the Lijiang River Basin, China. We selected a variety of bias correction methods and their combinations to correct the lower resolution GCM outputs of both precipitation and temperature. Then, the SWAT model was calibrated and validated using the observed flow data and corrected historical GCM with the optimal correction method selected. Hydrological variables were simulated using the SWAT model under emission scenarios RCP2.6, RCP4.5, and RCP8.5. The results demonstrated that correcting methods have a positive effect on both daily precipitation and temperature, and a hybrid method of bias correction contributes to increased performance in most cases and scenarios. Based on the bias corrected scenarios, precipitation annual average, temperature, and evapotranspiration will increase. In the case of precipitation and runoff, projection scenarios show an increase compared with the historical trends, and the monthly distribution of precipitation, evapotranspiration, and runoff shows an uneven distribution compared with baseline. This study provides an insight on how to choose a proper GCM and bias correction method and a helpful guide for local water resources management.

In the current research, gene expression programming (GEP) was applied to model reference evapotranspiration (ETo) in 18 regions of Iran with limited meteorological data. Initially, a genetic algorithm (GA) was employed to detect the most important variables for estimating ETo among mean temperature (Tmean), maximum temperature (Tmax), minimum temperature (Tmin), relative humidity (RH), sunshine (n), and wind speed (WS). The results indicated that a coupled model containing the Tmean and WS can predict ETo accurately (RMSE = 0.3263 mm day−1) for arid, semiarid, and Mediterranean climates. Therefore, this model was adjusted using the GEP for all 18 synoptic stations. Under very humid climates, it is recommended to use a temperature-based GEP model versus wind speed-based GEP model. The optimal and lowest performance of the GEP belonged to Shahrekord (SK), RMSE = 0.0650 mm day−1, and Kerman (KE), RMSE = 0.4177 mm day−1, respectively. This research shows that the GEP is a robust tool to model ETo in semiarid and Mediterranean climates (R2 > 0.80). However, GEP is recommended to be used cautiously under very humid climates and some of arid regions (R2 < 0.50) due to its poor performance under such extreme conditions.