Tomato production systems in Florida are typically intensively managed with high inputs of fertilizer and irrigation and on sandy soils with low inherent water and nutrient retention capacities; ...potential nutrient leaching losses undermine the sustainability of such systems. The objectives of this 3-year field study were to evaluate the interaction between N-fertilizer rates and irrigation scheduling on crop N and P accumulation, N-fertilizer use efficiency (NUE) and NO
3–N leaching of tomato cultivated in a plastic mulched/drip irrigated production system in sandy soils. Experimental treatments were a factorial combination of three irrigation scheduling regimes and three N-rates (176, 220, and 330
kg
ha
−1). Irrigation treatments included were: (1) surface drip irrigation (SUR) both the irrigation and fertigation line placed underneath the plastic mulch; (2) subsurface drip irrigation (SDI) where the irrigation drip was placed 0.15
m below the fertigation line which was located on top of the bed; and (3) TIME (conventional control) with the irrigation and fertigation lines placed as in SUR and irrigation applied once a day. Except for the TIME treatment all irrigation treatments were soil moisture sensor (SMS)-based with irrigation occurring at 10% volumetric water content. Five irrigation windows were scheduled daily and events were bypassed if the soil water content exceeded the established threshold. The use of SMS-based irrigation systems significantly reduced irrigation water use, volume percolated, and nitrate leaching. Based on soil electrical conductivity (EC) readings, there was no interaction between irrigation and N-rate treatments on the movement of fertilizer solutes. Total plant N accumulation for SUR and SDI was 12–37% higher than TIME. Plant P accumulation was not affected by either irrigation or N-rate treatments. The nitrogen use efficiency for SUR and SDI was on the order of 37–45%, 56–61%, and 61–68% for 2005, 2006 and 2007, respectively and significantly higher than for the conventional control system (TIME). Moreover, at the intermediate N-rate SUR and SDI systems reduced NO
3–N leaching to 5 and 35
kg
ha
−1, while at the highest N-rate corresponding values were 7 and 56
kg
N
ha
−1. Use of N application rates above 220
kg
ha
−1 did not result in fruit and/or shoot biomass nor N accumulation benefits, but substantially increased NO
3–N leaching for the control treatment, as detected by EC monitoring and by the lysimeters. It is concluded that appropriate use of SDI and/or sensor-based irrigation systems can sustain high yields while reducing irrigation application as well as reducing NO
3–N leaching in low water holding capacity soils.
•Water content sensors placement for drip irrigation scheduling in layered soils is studied.•A specially developed mathematical model incorporating a system-dependent boundary condition was used.•In ...layered soils at least two sensors are needed to obtain representative water content readings.•In optimum positions for pairs of sensors one sensor should be positioned in each soil layer.•Soil water content probes penetrating both soil layers may also provide representative readings.
Efficient irrigation management requires a sound information basis; therefore, various environmental measurements are currently used in irrigation scheduling. Among other technics, the recent progress in electromagnetic sensors technologies promoted the development of automated irrigation scheduling systems based on soil water content sensors with very promising results in terms of water savings. However, a key factor for the adequate performance of such systems is proper placement of soil moisture sensors. Up to now, sensor placement guidelines are fragmentary or empirically determined from site and crop specific experiments. This study aims to extend the findings of previous studies investigating the issue of proper positioning of water content sensors in drip irrigation scheduling systems in uniform soils for the case of layered soils. In this context the representativeness of soil water content sensors’ readings and the existence of Time Stable Representative Positions (TSRP) are investigated using a specially developed mathematical model. The use of soil water content probes that are able to monitor soil water content at various depths is also evaluated. It was found that in contrast to the previous findings concerning uniform soils, in the case of layered soils it is not possible to precisely monitor the average soil water content temporal variation in the root zone using a single sensor; however, it is feasible to achieve this using a pair of sensors. Furthermore, common optimum positions for a pair of sensors providing representative soil water content readings independently from the prevailing conditions and the irrigation system configuration can be identified. It was also found that soil water content probes covering the average rooting depth and penetrating both soil layers are also able to provide representative soil water content readings during the whole duration of the irrigation cycle. The above results represent a further step towards the development of general guidelines for sensor placement in soil water content based surface drip irrigation scheduling systems.
Steep slopes covered by loose unsaturated pyroclastic deposits widely dispersed in Campania, Southern Italy, are often subjected to shallow landslides that turn into fast debris flows causing a large ...amount of damage and many casualties, triggered by heavy and persistent precipitation. The slope of Cervinara, located around 40 km northeast of Naples, was involved in a destructive flowslide between 15 and 16 December 1999, triggered by a rain event of 325 mm in 48 h. Hydrometeorological monitoring activities have been carried out near the landslide scarp of 1999 since 2017 to assess the water balance and to identify major hydrological processes involving the cover and the shallow groundwater system developing in the upper part of the underlying limestone fractured bedrock. Since 1 December 2022, a remotely accessible low-cost network has been installed to expand the field hydrological monitoring. The use of a network of low-cost capacitive sensors, communicating within the domain of Internet of Things (IoT) technology, aiming at dispersed monitoring of soil moisture, has been tested. Specifically, the tested prototype network allows measurements of the soil water content at two different points, communicating through a Wi-Fi-based IoT system using ESP32 boards. The ThingSpeak
IoT platform has been used for remote field data visualization. Based on the obtained results, the prototype of this IoT-based low-cost network shows the potential to expand the amount of hydrological data, suitable for setting up early warning systems in landslide-prone areas.
This work aimed to assess the recalibration and accurate characterization of commonly used smart soil-moisture sensors using computational methods. The paper describes an ensemble learning algorithm ...that boosts the performance of potato root moisture estimation and increases the simple moisture sensors’ performance. It was prepared using several month-long everyday actual outdoor data and validated on the separated part of that dataset. To obtain conclusive results, two different potato varieties were grown on 24 separate plots on two distinct soil profiles and, besides natural precipitation, several different watering strategies were applied, and the experiment was monitored during the whole season. The acquisitions on every plot were performed using simple moisture sensors and were supplemented with reference manual gravimetric measurements and meteorological data. Next, a group of machine learning algorithms was tested to extract the information from this measurements dataset. The study showed the possibility of decreasing the median moisture estimation error from 2.035% for the baseline model to 0.808%, which was achieved using the Extra Trees algorithm.
•Proposed a conductivity compensation method for detecting moisture at LF.•Two kinds of probes for measuring capacitance and conductivity were designed.•Designed a real-time monitoring system which ...can be used in field application.•Establish the optimized mathematical model based on capacitance and conductivity.
The detection of soil moisture is one of the most important researches in the development of precision agriculture. At present, the detection of soil dielectric constant is the most effective and convenient method to measure soil moisture content. Most of the dielectric type soil moisture sensors reduce the influence of soil salinity, texture and other factors on the measurement by detecting at high frequency. However, this will increase the production cost of the measurement circuit and fail to meet the requirements for large-scale deployment of sensors in agricultural production. The method of low-frequency capacitance detection has a price advantage but a low measurement accuracy, thus the application is very limited. This paper intends to improve the measurement accuracy and application range of low-frequency capacitance moisture sensors by correcting the relationship between low-frequency capacitance and moisture through the detection of soil conductivity. Three modified models (logistic, exponential and polynomial) to estimate the moisture content was verified by comparing with the oven-drying method calibration value. The results indicated that the MAME and MAE of the logistic model was less than 3.55% and 2.50%, respectively, which can satisfy most agricultural production requirements for soil moisture detection. Therefore, the study provided an effective detection method for low-cost soil moisture detection in low salinity and low organic matter soils.
•We present the first soil moisture sensor integrated with a TEG.•Thermosensitive resistors present linear and high TC, typically −16, 000ppm/°C.•Low-cost process with nanocrystals particles printed ...on the TEG substrate.•Sensor with high sensitivity, about 37% better than sensors previously published.•Technology opens the doors to sensors based on nanoparticles integrated with TEGs.
An autonomous single heat pulse probe porous ceramic soil moisture sensor powered by a thermoelectric generator (TEG) is presented. The sensor uses nanostructured thermosensitive resistors fabricated on the same ceramic substrate of the TEG. The nanostructured resistors, fabricated by printing PbS quantum dots, present a very high thermal coefficient (−16×103ppm/°C) and, used in a bridge configuration with conventional precision and low thermal coefficient SMD metal film resistors, result in a high sensitivity temperature sensor. A laboratory prototype of the sensor showed a voltage variation of 2.4mV in the output of the bridge when the volumetric water content of the soil changed from 5% to 40%. To complete the autonomous system, we designed an ultra low-power electronic interrogator which, when powered only by the 3 F supercapacitor of the integrated TEG energy harvesting system, was able to take daily measurements up to 5 days without harvesting energy.
The amount of surface soil moisture (SSM) is a crucial ecohydrological natural resource that regulates important land surface processes. It affects critical land–atmospheric phenomena, including the ...division of energy and water (infiltration, runoff, and evaporation), that impacts the effectiveness of agricultural output (sensible and latent heat fluxes and surface air temperature). Despite its significance, there are several difficulties in making precise measurements, monitoring, and interpreting SSM at high spatial and temporal resolutions. The current study critically reviews the methods and procedures for calculating SSM and the variables influencing measurement accuracy and applicability under different fields, climates, and operational conditions. For laboratory and field measurements, this study divides SSM estimate strategies into (i) direct and (ii) indirect procedures. The accuracy and applicability of a technique depends on the environment and the resources at hand. Comparative research is geographically restricted, although precise and economical—direct measuring techniques like the gravimetric method are time-consuming and destructive. In contrast, indirect methods are more expensive and do not produce measurements at the spatial scale but produce precise data on a temporal scale. While measuring SSM across more significant regions, ground-penetrating radar and remote sensing methods are susceptible to errors caused by overlapping data and atmospheric factors. On the other hand, soft computing techniques like machine/deep learning are quite handy for estimating SSM without any technical or laborious procedures. We determine that factors, e.g., topography, soil type, vegetation, climate change, groundwater level, depth of soil, etc., primarily influence the SSM measurements. Different techniques have been put into practice for various practical situations, although comparisons between them are not available frequently in publications. Each method offers a unique set of potential advantages and disadvantages. The most accurate way of identifying the best soil moisture technique is the value selection method (VSM). The neutron probe is preferable to the FDR or TDR sensor for measuring soil moisture. Remote sensing techniques have filled the need for large-scale, highly spatiotemporal soil moisture monitoring. Through self-learning capabilities in data-scarce areas, machine/deep learning approaches facilitate soil moisture measurement and prediction.
Palmer amaranth (Amaranthus palmeri S. Watson) is the most problematic weed in agronomic crop production fields in the United States. The objective of this study was to determine the effect of degree ...of water stress on the growth and fecundity of A. palmeri using soil moisture sensors under greenhouse conditions. Two A. palmeri biotypes collected from Nebraska were grown in loam soil maintained at 100%, 75%, 50%, 25%, and 12.5% soil field capacity (FC) corresponding to no, light, moderate, high, and severe water stress levels, respectively. Water was regularly added to pots based on soil moisture levels detected by Watermark or Decagon 5TM sensors to maintain the desired water stress level. Amaranthus palmeri plants maintained at ≤25% FC did not survive more than 35 d after transplanting. Amaranthus palmeri at 100%, 75%, and 50% FC produced similar numbers of leaves (588 to 670 plant− 1) based on model estimates; however, plants at 100% FC achieved a maximum height of 178 cm compared with 124 and 88 cm at 75% and 50% FC, respectively. The growth index (1.1 × 105 to 1.4 × 105 cm3 plant − 1) and total leaf area (571 to 693 cm2 plant − 1) were also similar at 100%, 75%, and 50% FC. Amaranthus palmeri produced similar root biomass (2.3 to 3 g plant − 1) at 100%, 75%, and 50% FC compared with 0.6 to 0.7 g plant − 1 at 25% and 12.5% FC, respectively. Seed production was greatest (42,000 seeds plant − 1) at 100% FC compared with 75% and 50% FC (14,000 to 19,000 seeds plant − 1); however, the cumulative seed germination was similar (38% to 46%) when mother plants were exposed to ≥50% FC. The results of this study show that A. palmeri can survive ≥50% FC continuous water stress conditions and can produce a significant number of seeds with no effect of on seed germination.
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