Frequency Domain Reflectometry Sensors Research Articles

Spatial and Temporal Distribution of Soil Moisture in Maize Using Frequency Domain Reflectometry Sensor

Field experiment was conducted during kharif 2018, rabi 2018-19 and kharif 2019 at Department of Soil Water Engineering, Dr. NTR College of Agricultural Engineering, Bapatla, Andhra Pradesh to study the spatial and temporal distribution of soil moisture in maize using FDR sensor.The experiment was laid out in split plot design consisting of three irrigation levels (0.6 ETc (I1), 0.8 ETc (I2) and 1.0 ETc (I3)) and four nitrogen levels consisting of fertigation levels (80% RDN (N1), 100% RDN (N2), 120% RDN (N3) and Manual application (N4) on sandy clay loam soil. Water requirement of the maize crop was calculated on the daily basis by using CROPWAT 8.0. Frequency Domain Reflectometry (FDR) Sensor was used to measure soil moisture data by installing 34 access tubes up to a depth of 100 cm with an interval of 10 cm from the soil surface and measured soil water content during crop period. Soil moisture was evaluated for 2.0 lph emitter discharges at 3h after irrigation, 6h after irrigation, 24h after irrigation at emitter, 15 cm from emitter, 30 cm from emitter and 45 cm from emitter for soil moisture in the soil for arriving the best irrigation strategy. The soil water distribution under all drip irrigation treatments indicated that it was relatively high near the dripper and decreased as the distance from the dripper point increased.

Calculation of soil water content using dielectric-permittivity-based sensors – benefits of soil-specific calibration

Abstract. Soil water content (SWC) sensors are widely used for scientific studies or for the management of agricultural practices. The most common sensing techniques provide an estimate of volumetric soil water content based on sensing of dielectric permittivity. These techniques include frequency domain reflectometry (FDR), time domain reflectometry (TDR), capacitance and even remote-sensing techniques such as ground-penetrating radar (GPR) and microwave-based techniques. Here, we will focus on frequency domain reflectometry (FDR) sensors and more specifically on the questioning of their factory calibration, which does not take into account soil-specific features and therefore possibly leads to inconsistent SWC estimates. We conducted the present study in the southwest of France on two plots that are part of the ICOS ERIC network (Integrated Carbon Observation System, European Research and Infrastructure Consortium), FR-Lam and FR-Aur. We propose a simple protocol for soil-specific calibration, particularly suitable for clayey soil, to improve the accuracy of SWC determination when using commercial FDR sensors. We compared the sensing accuracy after soil-specific calibration versus factory calibration. Our results stress the necessity of performing a thorough soil-specific calibration for very clayey soils. Hence, locally, we found that factory calibration results in a strong overestimation of the actual soil water content. Indeed, we report relative errors as large as +115 % with a factory-calibrated sensor based on the real part of dielectric permittivity and up to + 245 % with a factory-calibrated sensor based on the modulus of dielectric permittivity.

Smart Polymer Composite Deck Monitoring Using Distributed High Definition and Bragg Grating Fiber Optic Sensing.

Fiber-reinforced polymer composites are an excellent choice for bridge decks due to high strength, lightweight, resistance to corrosion, and long-term durability with a 100-year design life. Structural health monitoring is useful for the long-term assessment of the condition of the bridge structure and obtaining a response to complex loads considering environmental conditions. Bridge structures have been studied primarily using distributed fiber optic sensing, such as Brillouin scattering; however, critical events, including damage detection, can be missed due to low spatial resolution. There is also a critical need to conduct a comprehensive study of static and dynamic loading simultaneously for fiber-reinforced composite bridge structures. In this study, a novel approach was implemented using two sensor technologies, optical frequency domain reflectometry and fiber Bragg grating-based sensors, embedded in a glass-fiber-reinforced composite bridge deck to simultaneously monitor the deformation response of the bridge structure. The optical frequency domain reflectometry sensor utilizing Rayleigh scattering provides high spatial strain resolution were positioned strategically based on expected stress distributions to measure strain in the longitudinal, transverse, and diagonal directions along the span of the composite bridge. Furthermore, fiber Bragg grating based sensors are used to monitor the response to dynamic vehicular loading and deformations from an automotive-crash-type event on the bridge structure. To monitor environmental variables such as temperature, a custom wireless configured sensor package was developed for the study and integrated with a composite bridge located in Morgan County, Tennessee. Additionally, a triaxial accelerometer was used to monitor the vehicular dynamic loading of the composite bridge deck in parallel with fiber Bragg grating sensors. When appropriate, mid-point displacements were compared with strain-distribution measurements from the fiber optic sensor-based data.

Moisture Migration and Control of New Embankment for Reconstruction and Expansion Project in Southern China

In hot and humid regions of southern China, the volumetric moisture content of the embankment after opening to traffic for a period of time reaches a stable state, and it is higher than the design value. When it was widened, the humidity gradient and exchange were formed due to the difference in moisture content between the existing and new embankment. To reveal the moisture migration of the existing and new embankment and control the rise of volumetric moisture content in new embankment, six frequency domain reflectometry sensors were installed in existing and new embankment to monitor the volumetric moisture content. A finite element model for the embankment was established and verified with the measured data. And seven numerical analyses of transient seepage in the new embankment of the cushion, cover, and partition using capillary barrier by sand were simulated. The results show that the volumetric moisture contents of the new embankment in southern China gradually increase and eventually reach an equilibrium state. The increase in water comes from the slope, the foundation, and the existing embankment. Early in the first 1∼2 years, the water mainly comes from the foundation and the existing embankment. After that, as time goes by, the water comes mostly from the slope infiltration and gradually migrates to the foundation and the existing embankment. Finally, the volumetric moisture content and the water storage gradually reach equilibrium. The volumetric moisture content of the new embankment using capillary barrier by sand at the cushion, the cover, and the partition is maintained as the construction volumetric moisture content. This combination is a very effective method to control the humidity stability of the new embankment in southern China.

Numerical simulation of the moisture migration of unsaturated clay embankments in southern China considering stress state

To determine the moisture contents of unsaturated clay embankments in southern China considering the stress state, 753 moisture data of three existing embankments for about 20 years were measured, and six frequency domain reflectometry sensors were installed in a widened embankment in southern China to monitor the moisture content. The soil water characteristic curve (SWCC) and stress-dependent soil water characteristic curves (SDSWCCs) were determined in the laboratory using a pressure plate apparatus and a stress-dependent parametric equation was established. The finite element model of a typical unsaturated clay embankment in southern China considering the SWCC and SDSWCCs was created. Then, the variation of the moisture contents of the clay embankment was simulated. The results show that the vertical stress has an obvious effect on the moisture distribution in embankments, especially the positions inside embankments where the vertical stress is large and cannot be neglected. The finite element model considering the SDSWCCs, therefore, should be selected when analyzing the moisture filed of embankments in southern China. For the existing clay embankments in southern China, their moisture contents gradually increase from the optimum moisture content to equilibrium values, which is close to the plastic limit and increases by 99% of the optimum moisture content. In addition, the resilient modulus values at different locations of the embankment and that of the whole embankment are reduced by 55 to 62%. And the safety factor of the slope obviously decreases, and its reduction is greater than 60%.

A Machine Learning Method to Estimate Reference Evapotranspiration Using Soil Moisture Sensors

One of the most important applications of remote imaging systems in agriculture, with the greatest impact on global sustainability, is the determination of optimal crop irrigation. The methodology proposed by the Food and Agriculture Organization (FAO) is based on estimating crop evapotranspiration (ETc), which is done by computing the reference crop evapotranspiration (ETo) multiplied by a crop coefficient (Kc). Some previous works proposed methods to compute Kc using remote crop images. The present research aims at complementing these systems, estimating ETo with the use of soil moisture sensors. A crop of kikuyu grass (Pennisetum clandestinum) was used as the reference crop. Four frequency-domain reflectometry sensors were installed, gathering moisture information during the study period from May 2015 to September 2016. Different machine learning regression algorithms were analyzed for the estimation of ETo using moisture and climatic data. The values were compared with respect to the ETo computed in an agroclimatic station using the Penman–Monteith method. The best method was the randomizable filtered classifier technique, based on the K* algorithm. This model achieved a correlation coefficient, R, of 0.9936, with a root-mean-squared error of 0.183 mm/day and 6.52% mean relative error; the second-best model used artificial neural networks, with an R of 0.9470 and 11% relative error. Thus, this new methodology allows obtaining accurate and cost-efficient prediction models for ETo, as well as for the water balance of the crops.

Standardization of Frequency Domain Reflectometry and Watermark Sensors for Soil Moisture Measurement at Field Level

A field experiment with spilt plot design was carried out for standardization of Frequency Domain Reflectometry (FDR) and Watermark sensors in drip irrigated broccoli(Brassica oleracea var. italica). The experiment included three levels of irrigation frequencies: N1 (once every day), N2 (once every 2 days) and N3 (once every 3 days) with three irrigation regimes of 100, 80 and 60 % of crop evapotranspiration (ETc). For evaluating the performance of different soil moisture sensors, the sensors’ readings were taken from the plot on a daily basis and these readings were compared with gravimetric methods (standard). It was observed that the calibration of two sensors (FDR and Watermark) give a similar calibration equation with lowRMSE after field calibration. The value of coefficient of determination (R2) for FDR was observed 0.85, 0.86, 0.89 and 0.86 for 0-15, 15-30, 30-45 and 45-60 cm soil depth whereas, the value of coefficient of determination (R2) for Watermark sensor was observed as 0.76, 0.83, 0.84 and 0.85 for 0-15, 15-30, 30-45 and 45-60 cm soil depth, respectively. The Watermark sensorscurves observed less sensitive at low soil water tension,whereas FDR sensors performed better in wet as well as dry conditions. That field calibrationof soil moisture sensors isa prerequisite to measure soil moisture content in the soil.

Development of pot-cover effect apparatus with freezing-thawing cycles

‘Pot-cover effect’ refers to the phenomenon of moisture accumulation beneath the pavement under condensation or desublimation because the vapor transfer in the soil is blocked by the pavement. To study this phenomenon in the laboratory, we have developed the pot-cover effect apparatus with freezing-thawing cycles (PEAFC), which consists of three parts, namely, the vapor transfer system, the temperature control system, and the temperature and water content monitoring system. The major functions of this apparatus include: simulation of both vapor transfer and freezing-thawing cycling in the soil, real-time monitoring of the temperature and the water content in soil samples, and one-dimensional heat and moisture transfer in the samples. The FDR (frequency domain reflectometry) sensors of the apparatus are calibrated and a calibration formula is proposed to eliminate the water content measurement errors induced by temperature changes. Constant temperature difference tests and a freezing-thawing cycling test are conducted with the apparatus. Results indicate that the apparatus can control the water replenishment in the soil samples, monitor the vapor transfer in the samples in real time, and simulate the vapor transfer process under the condition of the freezing-thawing cycling in the soil. These tests verify the effectiveness and reliability of the apparatus, which indicates that the development purpose is achieved.

Application of EMI and FDR Sensors to Assess the Fraction of Transpirable Soil Water over an Olive Grove

Accurate soil water status measurements across spatial and temporal scales are still a challenging task, specifically at intermediate spatial (0.1–10 ha) and temporal (minutes to days) scales. Consequently, a gap in knowledge limits our understanding of the reliability of the spatial measurements and its practical applicability in agricultural water management. This paper compares the cumulative EM38 (Geonics Ltd., Mississauga, ON, Canada) response collected by placing the sensor above ground with the corresponding soil water content obtained by integrating the values measured with an FDR (frequency domain reflectometry) sensor. In two field areas, characterized by different soil clay content, two Diviner 2000 access tubes (1.2 m) were installed and used to quantify the dimensionless fraction of transpirable soil water (FTSW). After the calibration, the work proposes the combined use of the FDR and electromagnetic induction (EMI) sensors to measure and map FTSW. A strong correlation (R2 = 0.86) between FTSW and EM38 bulk electrical conductivity was found. As a result, field changes of FTSW are due to the variability of soil water content and soil texture. As with the data acquired in the field, more structured patterns occurred after a wetting event, indicating the presence of subsurface flow or root water uptake paths. After assessing the relationship between the soil and crop water status, the FTSW domain includes a critical value, estimated around 0.38, below which a strong reduction of relative transpiration can be recognized.

Determining hydrological regimes in an agriculturally used tropical inland valley wetland in Central Uganda using soil moisture, groundwater, and digital elevation data

AbstractInadequate knowledge exists on the distribution of soil moisture and shallow groundwater in intensively cultivated inland valley wetlands in tropical environments, which are required for determining the hydrological regime. This study investigated the spatial and temporal variability of soil moisture along 4 hydrological positions segmented as riparian zone, valley bottom, fringe, and valley slope in an agriculturally used inland valley wetland in Central Uganda. The determined hydrological regimes of the defined hydrological positions are based on soil moisture deficit calculated from the depth to the groundwater table. For that, the accuracy and reliability of satellite‐derived surface models, SRTM‐30m and TanDEM‐X‐12m, for mapping microscale topography and hydrological regimes are evaluated against a 5‐m digital elevation model (DEM) derived from field measurements. Soil moisture and depth to groundwater table were measured using frequency domain reflectometry sensors and piezometers installed along the hydrological positions, respectively. Results showed that spatial and temporal variability in soil moisture increased significantly (p < .05) towards the riparian zone; however, no significant difference was observed between the valley bottom and riparian zone. The distribution of soil hydrological regimes, saturated, near‐saturated, and nonsaturated regimes does not correlate with the hydrological positions. This is due to high spatial and temporal variability in depth to groundwater and soil moisture content across the valley. Precipitation strongly controlled the temporal variability, whereas microscale topography, soil properties, distance from the stream, anthropogenic factors, and land use controlled the spatial variability in the inland valley. TanDEM‐X DEM reasonably mapped the microscale topography and thus soil hydrological regimes relative to the Shuttle Radar Topography Mission DEM. The findings of the study contribute to improved understanding of the distribution of hydrological regimes in an inland valley wetland, which is required for a better agricultural water management planning.

Hydrologic and Geochemical Research at Pinios Hydrologic Observatory: Initial Results

Core Ideas Modeled ETo gradients present variations as a function of altitude, annual cycle, and total amount. A very good match between different soil moisture monitoring devices has been achieved. Groundwater level monitoring revealed dominant hydrodynamic evolution mechanisms. Hydrochemical monitoring supports groundwater hydrology findings and reveals pollution sources. Monitoring the PHO supports accurate hydrologic modeling and sustainable water use. The Pinios Hydrologic Observatory (PHO) is located in the River Pinios basin, which is one of the most productive basins in Greece. The PHO was established to develop deep knowledge of water balance at the river basin scale and to improve understanding of the major hydrodynamic mechanisms to improve hydrological modeling and ultimately sustainable water resource management. The PHO comprises three meteorological stations, 12 groundwater monitoring sites, and one soil moisture monitoring site, which includes frequency domain reflectometry sensors (SoilNet) and a cosmic‐ray neutron sensor (CRNS) probe. Although the PHO was recently established (at the end of 2015), the preliminary findings from data analysis are promising. Calculated reference evapotranspiration (ETo) gradients demonstrate differences regarding their annual cycle, total amount, and altitude level. Moreover, climate analysis indicates nocturnal mountain‐valley winds. Groundwater level spatial distribution indicates the dominant recharge mechanisms to the alluvial aquifer system. These findings are also supported by the hydrochemical data analysis (electrical conductivity and, secondarily, NO3 distribution). Locally elevated NO3 concentrations are attributed to agricultural activities and call for review of the adopted farming practices. Results from the soil moisture monitoring site indicate a very good match between the CRNS probe and the average SoilNet data. Future perspectives of the PHO include geophysical surveys to accurately delineate the geometry of the groundwater system, the expansion of groundwater and soil moisture observation networks, and the application of the mGROWA hydrologic model to accurately simulate the hydrological processes in the PHO and upscale in the entire River Pinios basin. Finally, in support of the local farmers, we plan to develop and implement a distributed irrigation programming protocol in the entire area of the PHO.

Influence of soil moisture content on assessment of bulk density with combined frequency domain reflectometry and visible and near infrared spectroscopy under semi field conditions

The potential of combining frequency domain reflectometry (FDR) and visible and near infrared spectroscopy (vis-NIRS) was shown to successfully assess soil bulk density (BD). However, the accuracy of both sensing tools was reported to be influenced by the soil moisture content (MC). The aim of the paper is to evaluate the influence of soil MC level on accuracy of BD assessment under semi field conditions by the combination of FDR and vis-NIRS data. Measurements of volumetric moisture content (θv) in the field and gravimetric moisture content (ω) in the laboratory using a FDR and a vis-NIRS (350–2500nm) techniques were conducted in five arable fields of different soil texture classes in Silsoe, Bedfordshire, UK. In order to account for different MC levels, three measurement campaigns were carried out during the period from July 2011 to October 2012, where a total of 300 soil samples were used, representing three natural MC levels of low (L1), medium (L2) and high (L3). L1, L2 and L3 datasets were subjected to artificial neural network (ANN) analysis to predict ω and θv based on fusion of vis-NIRS spectra and FDR output voltage, and subsequently the predicted values were substituted into a model to assess BD.Results showed that MC has large influence on both the vis-NIRS and FDR sensors for measuring ω and θv, respectively. The accuracy of BD assessment improved with soil MC increase, with root mean square error of prediction (RMSEp) values of 0.079, 0.072 and 0.061 g cm−3, for average ω of 0.106 (L1), 0.197 (L2) and 0.28 (L3) gg−1, respectively. The accuracy of θv measurement with the FDR depended on ensuring good contact with the soil, which is not the case for dry soil conditions, at which accuracy of θv measurement and BD assessment was deteriorated. It is recommended to set an optimal MC range (depending of soil texture), over which precise soil BD estimation can be certain.

Monitoring water content dynamics of biological soil crusts

Biological soil crusts (hereafter, “biocrusts”) dominate soil surfaces in nearly all dryland environments. To better understand the influence of water content on carbon (C) exchange, we assessed the ability of dual-probe heat-pulse (DPHP) sensors, installed vertically and angled, to measure changes in near-surface water content. Four DPHP sensors were installed in each of two research plots (eight sensors total) that differed by temperature treatment (control and heated). Responses were compared to horizontally installed water content measurements made with three frequency-domain reflectometry (FDR) sensors in each plot at 5-cm depth. The study was conducted near Moab, Utah, from April through September 2009. Results showed significant differences between sensor technologies: peak water content differences from the DPHP sensors were approximately three times higher than those from the FDR sensors; some of the differences can be explained by the targeted monitoring of biocrust material in the shorter DPHP sensor and by potential signal loss from horizontally installed FDR sensors, or by an oversampling of deeper soil. C-exchange estimates using the DPHP sensors showed a net C loss of 69 and 76 g C m−2 in control and heated plots, respectively. The study illustrates the potential for using the more sensitive data from shallow installations for estimating C exchange in biocrusts.

A distributed parameters model for soil water content: Spatial and temporal variability analysis

Soil water content is the main limiting factor for plant development under arid or semi-arid climates. Furthermore, it is a key factor in the physical, chemical and biological processes that occur in the soil-plant-atmosphere system; acting as a vector between these components. A distributed parameters model is proposed in order to describe the spatiotemporal variability of soil water content, linking the soil water content with the system inputs, such as rain or irrigation water, and the system outputs: evaporation, transpiration and percolation losses. Adding the lateral exchanges and the surface runoff makes it possible to take into account the terrain orography and tessellation. An experimental plot in SW Spain was used, where Soil Water Content was monitored with frequency-domain reflectometry sensors in several points, whereas the plot was divided into rectangular sectors. The rainfall was measured by a nearby agro-climatic station. A simulation environment was developed, using it to identify the model terms with experimental measurements and run other simulations for different climatic conditions.

Improving water and fertilizer use efficiency during the production of strawberry in coir substrate hydroponics using a FDR sensor-automated irrigation system

Water drainage from open hydroponic systems often causes significant environmental pollution (due to the use of agrochemicals) and leads to the loss of water and nutrients. The objective of this study was to investigate the potential application of an irrigation schedule based on previously determined threshold values of volumetric substrate water content to improve strawberry (Fragaria ananassa L. cv. ‘Seolhyang’) cultivation in a commercial hydroponic farm. Specifically, we aimed to improve water and fertilizer delivery in a coir substrate hydroponics system using frequency domain reflectometry (FDR) sensor-automated irrigation (FAI). For comparison, a conventional fixed timer-based irrigation (TIMER) treatment was applied. We observed a significant decrease in irrigation volume when strawberry plants were cultivated using FAI due to a reduced drainage ratio, whereas irrigation scheduling using TIMER consumed large amounts of nutrient solution. The weekly irrigation volume per plant for the experimental period averaged 370 mL for the FAI system and 666 mL for TIMER. The weekly drainage volume per plant averaged 55.8 mL for the FAI system and 300 mL for TIMER. The total irrigation volume for TIMER was 1.7-fold higher than that for FAI, while there was no significant difference in the total retained volume in the substrate between the two treatments during the experimental period, which led to a 1.2-fold higher WUE under FAI. Plant growth, fruit yield, and soluble solid content did not significantly differ between irrigation methods. The volumetric water contents in the substrate ranged from 58 to 62% and from 63 to 65% for FAI and TIMER, respectively. The EC level of the substrate solution (measured using an FDR sensor) ranged from 0.8 dS·m -1 to 1.4 dS·m -1 for both the FAI and TIMER systems. A cost savings of approximately 41% (for fertilizer) was achieved in FAI compared to TIMER. The FAI technique for coir substrate hydroponics can be utilized in large-scale hydroponic farms, resulting in the efficient and environmentally sustainable use of water and fertilizer.

Field Measurements and Numerical Simulations of Temperature and Moisture in Highway Engineering Using a Frequency Domain Reflectometry Sensor.

This paper presents a systematic pioneering study on the use of agricultural-purpose frequency domain reflectometry (FDR) sensors to monitor temperature and moisture of a subgrade in highway extension and reconstruction engineering. The principle of agricultural-purpose FDR sensors and the process for embedding this kind of sensors for subgrade engineering purposes are introduced. Based on field measured weather data, a numerical analysis model for temperature and moisture content in the subgrade’s soil is built. Comparisons of the temperature and moisture data obtained from numerical simulation and FDR-based measurements are conducted. The results show that: (1) the embedding method and process, data acquisition, and remote transmission presented are reasonable; (2) the temperature and moisture changes are coordinated with the atmospheric environment and they are also in close agreement with numerical calculations; (3) the change laws of both are consistent at positions where the subgrade is compacted uniformly. These results suggest that the data measured by the agricultural-purpose FDR sensors are reliable. The findings of this paper enable a new and effective real-time monitoring method for a subgrade’s temperature and moisture changes, and thus broaden the application of agricultural-purpose FDR sensors.

Multi-Bus Fiber Sensor Protection Network Operation With Robustness Analysis

This paper proposes a multi-bus fiber-optic sensor network, which could multiplex different types of fiber sensors, locate the failure position, and recover the sensing services of sensors in a network immediately and automatically to keep them working without being interrupted. It is composed of master and slave nodes, as well as working and backup fibers connecting them. We introduce the operation of the network and two light source distributions by explaining the internal structures of the master and slave nodes along with the sensor protection and the fault location process. Then, we analyze the probability distribution of working status for both distributions and propose a quantitative evaluation criterion called weighted average robustness for the robustness analysis of any fiber sensor network. Meanwhile, this paper demonstrates its feasibility by multiplexing three fiber sensor systems: a distributed fiber-optic vibration sensor based on dual Mach-Zehnder interferometer architecture; an optical frequency domain reflectometry sensor; and three Fiber Bragg Grating sensors in this network at the same time detecting different parameters. We test the performance of the network in three scenarios by fabricating failures of the sensing and backup fibers intentionally to prove the feasibility of the structure. Furthermore, all the status of the network will be uploaded to the human-computer interface of supervisory computer by the master processor through USB in real time. Operators can also control the network through the interface remotely.

Erratum to: Environmentally sustainable production of tomato in a coir substrate hydroponic system using a frequency domain reflectometry sensor

Erratum to: Environmentally sustainable production of tomato in a coir substrate hydroponic system using a frequency domain reflectometry sensor

Environmentally sustainable production of tomato in a coir substrate hydroponic system using a frequency domain reflectometry sensor

Open hydroponic systems are the most widely used hydroponic systems in Korea. However, water drainage from the open hydroponics often causes significant environmental pollution due to agrochemicals and loss of water and nutrients. The objectives of this study were to show the potential application of an irrigation schedule based on threshold values of volumetric substrate water content tomato (Solanum lycopersicum L. ‘Betatini’) cultivation in a commercial hydroponic farm. This study was performed for minimizing effluent from coir substrate hydroponics using a frequency domain reflectometry (FDR) sensor-automated irrigation (FAI), as compared with conventional timer-irrigation (TIMER) from the farmer’s experience. The irrigation volume and retained water volume in the substrate of the TIMER during autumn to winter cultivation were 6.1-fold and 2-fold higher, respectively, than those of the FAI with slightly higher fruit weight and no difference in plant growth in the TIMER. This resulted in 1.9-fold higher water use efficiency (WUE) in the FAI. The irrigation volume and retained water volume in the substrate of TIMER during spring to summer were 3.2-fold and 1.8-fold higher, respectively, than those of the FAI with no difference in fruit weight or plant growth between the two treatments, which led to a 1.9-fold higher WUE in FAI. Approximately 61% fertilizer cost savings and a substantial decrease in drained solution volume were observed for FAI compared to those with TIMER. The use of the FAI technique for a least-drainage hydroponic system can be achieved in a large-scale hydroponic farm, resulting in efficient and environmentally sustainable use of water and fertilizer.

Biomass and quality changes of forages along land use and soil type gradients in the riparian zone of Lake Naivasha, Kenya

The recession of the water level of Lake Naivasha has incrementally exposed land surfaces creating a chronosequential transect representing durations of 1–30 years of exposure to grazing. This chronosequence provides a unique model to study the effects of land use duration on resource availability and resource base quality. Particularly, pasture quality changes in the riparian land of tropical fresh water lakes have so far not been studied. We assessed the effect of the duration of exposure to grazing on the biomass production, crude protein content and energy quality of pastures in a 4×4 latin square design (4 chronosequence positions×4 soil types). Species composition was recorded and biomass was sampled at monthly intervals from February to August 2011. Soil moisture was recorded using frequency domain reflectometry sensors. Vegetation samples were analyzed for dry matter, nitrogen and metabolizable energy. Increased land use duration favored a shift in species dominance from Pennisetum clandestinum to Cynodon plectostachyus, which was associated with a reduction in dry matter yield and increased plant nitrogen content. All measured variables tended to be higher in soils formed on alluvial than in those formed on lacustrine deposits. Increased soil N and gravimetric moisture content stimulated biomass accumulation. The crude protein yield and metabolizable energy changed with phenological stages of the pasture and declined significantly towards maturity (seed setting of grasses). Continuous grazing and reduced soil moisture content, both during low rainfall and increased distance from the lake shore, affected the composition of pasture grasses as well as forage yield and quality. This may thus differentially affect the suitability of the riparian land as pasture ground and feed resource area for grazing animals.