Development of a Proximal Soil Sensing System for the Continuous Management of Acid Soil

The notion that agriculturally productive land may be treated as a relatively homogeneous resource at thewithin-field scale is not sound. This assumption and the subsequent uniform application of planting material,chemicals and/or tillage effort may result in zones within a field being under- or over-treated. Arising fromthese are problems associated with the inefficient use of input resources, economically significant yield losses,excessive energy costs, gaseous or percolatory release of chemicals into the environment, unacceptable long-term retention of chemicals and a less-than-optimal growing environment. The environmental impact of cropproduction systems is substantial. In this millennium, three important issues for scientists and agrariancommunities to address are the need to efficiently manage agricultural land for sustainable production, the maintenance of soil and water resources and the environmental quality of agricultural land.Precision agriculture (PA) aims to identify soil and crop attribute variability, and manage it in an accurate and timely manner for near-optimal crop production. Unlike conventional agricultural management where an averaged whole-field analytical result is employed for decision-making, management in PA is based on site-specific soil and crop information. That is, resource application and agronomic practices are matched with variation in soil attributes and crop requirements across a field or management unit. Conceptually PA makes economic and environmental sense, optimising gross margins and minimising the environmental impact of crop production systems. Although the economic justification for PA can be readily calculated, concepts such as environmental containment and the safety of agrochemicals in soil are more difficult to estimate. However,it may be argued that if PA lessens the overall agrochemical load in agricultural and non-agricultural environments, then its value as a management system for agriculture increases substantially.Management using PA requires detailed information of the spatial and temporal variation in crop yield components, weeds, soil-borne pests and attributes of physical, chemical and biological soil fertility. However,detailed descriptions of fine scale variation in soil properties have always been difficult and costly to perform.Sensing and scanning technologies need to be developed to more efficiently and economically obtain accurate information on the extent and variability of soil attributes that affect crop growth and yield. The primary aim of this work is to conduct research towards the development of an 'on-the-go' proximal soil pH and lime requirement sensing system for real-time continuous management of acid soil. It is divided into four sections.Section one consists of two chapters; the first describes global and historical events that converged into the development of precision agriculture, while chapter two provides reviews of statistical and geostatistical techniques that are used for the quantification of soil spatial variability and of topics that are integral to the concept of precision agriculture. The review then focuses on technologies that are used for the complete enumeration of soil, namely remote and proximal sensing.Section two comprises three chapters that deal with sampling and mapping methods. Chapter three provides a general description of the environment in the experimental field. It provides descriptions of the field site,topography, soil condition at the time of sampling, and the spatial variability of surface soil chemical properties. It also described the methods of sampling and laboratory analyses. Chapter four discusses some of the implications of soil sampling on analytical results and presents a review that quantifies the accuracy,precision and cost of current laboratory techniques. The chapter also presents analytical results that show theloss of information in kriged maps of lime requirement resulting from decreases in sample size. The messageof chapter four is that the evolution of precision agriculture calls for the development of 'on-the-go' proximal soil sensing systems to characterise soil spatial variability rapidly, economically, accurately and in a timely manner. Chapter five suggests that for sparsely sampled data the choice of spatial modelling and mapping techniques is important for reliable results and accurate representations of field soil variability. It assesses a number of geostatistical methodologies that may be used to model and map non-stationary soil data, in this instance soil pH and organic carbon. Intrinsic random functions of order k produced the most accurate and parsimonious predictions of all of the methods tested.Section three consists of two chapters whose theme pertains to sustainable and efficient management of acid agricultural soil. Chapter six discusses soil acidity, its causes, consequences and current management practices.It also reports the global extent of soil acidity and that which occurs in Australia. The chapter closes by proposing a real-time continuous management system for the management of acid soil. Chapter seven reports results from experiments conducted towards the development of an 'on-the-go' proximal soil pH and lime requirement sensing system that may be used for the real-time continuous management of acid soil. Assessment of four potentiometric sensors showed that the pH Ion Sensitive Field Effect Transistor (ISFET)was most suitable for inclusion in the proposed sensing system. It is accurate and precise, drift and hysteresis are low, and most importantly it's response time is small. A design for the analytical system was presented based on flow injection analysis (FIA) and sequential injection analysis (SIA) concepts. Two different modes of operation were described. Kinetic experiments were conducted to characterise soil:0.01M CaCl2 pH(pHCaCl2) and soil:lime requirement buffer (pH buffer) reactions. Modelling of the pH buffer reactions described their sequential, biphasic nature. A statistical methodology was devised to predict pH buffer measurements using only initial reaction measurements at 0.5s, 1s, 2s and 3s measurements. The accuracy of the technique was 0.1pH buffer units and the bias was low. Finally, the chapter describes a framework for the development of a prototype soil pH and lime requirement sensing system and the creative design of the system.The final section relates to the management of acid soil by liming. Chapter eight describes the development of empirical deterministic models for rapid predictions of lime requirement. The response surface models are based on soil:lime incubations, pH buffer measurements and the selection of target pH values. These models are more accurate and more practical than more conventional techniques, and may be more suitably incorporated into the spatial decision-support system of the proposed real-time continuous system for the management of acid soil. Chapter nine presents a glasshouse liming experiment that was used to authenticate the lime requirement model derived in the previous chapter. It also presents soil property interactions and soil-plant relationships in acid and ameliorated soil, to compare the effects of no lime applications, single-rate and variable-rate liming. Chapter X presents a methodology for modelling crop yields in the presence of uncertainty. The local uncertainty about soil properties and the uncertainty about model parameters were accounted for by using indicator kriging and Latin Hypercube Sampling for the propagation of uncertainties through two regression functions; a yield response function and one that equates resultant pH after the application of lime. Under the assumptions and constraints of the analysis, single-rate liming was found to be the best management option

Control of water supply and specific nutrient application in closed growing systems

Keywords:Tichelmann layout, constant drain flow, constant drain concentration, mass-flow, diffusion flow, sensor, Isfet, Chemfet, closed growing system, robust control, loopshaping, SimulinkÒ, MIMO controller, SISO controller, simplex routine, simplex matrix.Plants in modern greenhouses receive water and nutrients from a diluter of chemical solutes. Supply lines of a trickle irrigation system dispense the nutrient solution by means of thin capillary hoses, to each individual plant. Dependent on the type of growing system - either a NFT or a substrate system - the drain will run-off immediately or it will linger for some time in the substrate mat. In a closed system for water and nutrient supply, the drain water returns to the nutrient dispenser, where it is prepared for reuse by mixing it with clean water. The thesis starts with an overview of the state of the art of water supply and nutrient application systems.The purpose of the design study in this thesis is to enable completely closed growing systems for water and nutrients, to be applied in horticulture practise, and to improve the technological level of their control to such an extend that it is comparable to the level of computerised climate controllers in greenhouses. It is argued that as a basic requirement the system should have the ability to control the drain flow and the concentration of individual ions in the drain to any predefined set value. An analysis is given of the dynamics of movement of water and nutrients in substrates in relation to nutrient uptake, supply-flow and mass-flow. From a mass balance of nutrients, a control strategy for nutrient application in closed growing systems is suggested that is useful in the design of control algorithms. This strategy keeps the concentration of the individual ions in the drain constant by feedback of ion concentration and drain flow. In doing so, it compensates intrinsically for the plant's uptake of ions.The creation of a system with feedback control requires appropriate sensors and the ability to blend nutrient solution for values demanded by the controller. The ion specific feedback control of fertiliser application implies that ions need to be measured individually. The thesis describes a novel type of ion specific analyser, based on a set of Chemfet sensors. This instrument, as a result of this research, is the prototype of the first series of commercially available equipment for horticulture. Continuous measurement implies sensors with an electrical output, connected to an automatic data acquisition system with in-line calibration. In horticulture applications the lifetime expectancy of a sensor should at least be 6 to 9 months.In contrast to open loop control based on a prediction of uptake, feedback control automatically compensates for fluctuations in evapo-transpiration and nutrient uptake. Uptake by the plant is treated as a disturbance. Comparison of simulation results, with data from an implemented controller in a greenhouse, shows the success of the design.The so-called "Tichelmann" layout of supply lines is proposed to improve the dynamic properties of the supply system. The design study demonstrates and recommends robust controller design as a tool to achieve robust performance and robust stability as qualities of the controlled process to compensate for seasonal changes in the root mat or imperfect models. The modifications to the ideal design arising from the desire in practice for pulse wise water and nutrient injection, as well as aspects related to the blending are considered as well.</p

Optimization and Demonstration of In Situ Chemical Sensors for Marine Waters

The importance of autonomous in situ chemical sensors for ocean observations has increased drastically over the last decades. Yet, the huge potentials of sensor-based data collection remain underutilized by the scientific and regulatory communities, despite wider than ever usage of sensors. This thesis is part of a growing body of work to extend the usability of sensors and is embedded in the Ocean Best Practice approach, which could improve data quality in ocean observation in general. The here presented Ph.D. thesis covers multiple commercial sensors (LOC from ClearWater Sensors, Southampton, UK and OPUS from TriOS GmbH, Germany) for autonomous, high-resolution and in situ measurements of essential biogeochemical parameters (pH and nitrate) in marine waters. It was motivated by the necessity of improving the data quality of autonomous submersible optical sensors and broadening their utility. To achieve this, sensor deployments in various aquatic environments were conducted. Furthermore, the data obtained via sensors based on the same analytical principle was compared with each other, and with benchtop laboratory devices to assess the accuracy of the measurements. The achievements are associated with the acquisition of accurate and temporally well-resolved real-time data. A more reliable sensor-based data collection and improved deployability promotes a broader usage of autonomous sensors in general. Thus, a financially more sustainable ocean monitoring approach can be achieved, since a broader adaptation of autonomous sensors in research yields a higher cost efficiency

Leaf Eh and pH: A Novel Indicator of Plant Stress. Spatial, Temporal and Genotypic Variability in Rice (Oryza sativa L.)

A wealth of knowledge has been published in the last decade on redox regulations in plants. However, these works remained largely at cellular and organelle levels. Simple indicators of oxidative stress at the plant level are still missing. We developed a method for direct measurement of leaf Eh and pH, which revealed spatial, temporal, and genotypic variations in rice. Eh (redox potential) and Eh@pH7 (redox potential corrected to pH 7) of the last fully expanded leaf decreased after sunrise. Leaf Eh was high in the youngest leaf and in the oldest leaves, and minimum for the last fully expanded leaf. Leaf pH decreased from youngest to oldest leaves. The same gradients in Eh-pH were measured for various varieties, hydric conditions, and cropping seasons. Rice varieties differed in Eh, pH, and/or Eh@pH7. Leaf Eh increases and leaf pH decreases with plant age. These patterns and dynamics in leaf Eh-pH are in accordance with the pattern and dynamics of disease infections. Leaf Eh-pH can bring new insight on redox processes at plant level and is proposed as a novel indicator of plant stress/health. It could be used by agronomists, breeders, and pathologists to accelerate the development of crop cultivation methods leading to agroecological crop protection

Autonomous ocean carbon system observations from gliders

Climate change is altering the ocean carbonate system decreasing the seawater pH. To quantify these changes novel sampling and monitoring methods are necessary. One of these methods are gliders. The sensors to fit on a glider need to have a compact size, low-cost, stability, accuracy and fast response. For the first time, a CO2 optode (Aanderaa), a potentiometric pH glass electrode (Fluidion) and a spectrophotometric labon-chip pH sensor (UK National Oceanography Centre) were tested on gliders. The CO2 optode was deployed for 8 months in the Norwegian Sea, with an O2 optode. The CO2 measurements required several corrections. The calibrated optode CO2 concentrations and a regional parameterisation of total alkalinity (AT) were used to calculate dissolved inorganic carbon concentrations (CT) with a standard deviation of 11 μmol kg-1. The O2 and CO2 data were used to calculate CT- and O2-based net community production (NCP) from inventory changes combined with estimates of air-sea exchange, diapycnal mixing and entrainment of deeper waters. Because of the summer period the NCP was largely positive. The spectrophotometric pH sensor, the glass electrode and an O2 optode were deployed on a Seaglider for 10 days in the North Sea. Before the deployment, laboratory tests showed that the main source of error for glass electrodes is drift when deployed in seawater. The spectrophotometric sensor was stable with an accuracy of 0.002 and was used as reference to calibrate the glass electrode. The potentiometric sensor failed after 2 days' deployment and was not affected by drift (<0.01), because it had been stored in seawater for 2 months. The spectrophotometric sensor had a mean bias of 0.006±0.008 (1σ) compared with pH derived from discrete AT and CT samples, higher than in the laboratory. The data were used to calculate O2 and CO2 air-sea fluxes and bottom respiration rates

Aquatic biogeochemical eddy covariance fluxes in the presence of waves

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Long, M. H. Aquatic biogeochemical eddy covariance fluxes in the presence of waves. Journal of Geophysical Research: Oceans, 126(2), (2021): e2020JC016637, https://doi.org/10.1029/2020JC016637.The eddy covariance (EC) technique is a powerful tool for measuring atmospheric exchange rates that was recently adapted by biogeochemists to measure aquatic oxygen fluxes. A review of aquatic biogeochemical EC literature revealed that the majority of studies were conducted in shallow waters where waves were likely present, and that waves biased sensor and turbulence measurements. This review identified that larger measurement heights shifted turbulence to lower frequencies, producing a spectral gap between turbulence and wave frequencies. However, some studies sampled too close to the boundary to allow for a spectral turbulence‐wave gap, and a change in how EC measurements are conducted and analyzed is needed to remove wave‐bias. EC fluxes have only been derived from the time‐averaged product of vertical velocity and oxygen, often resulting in wave‐bias. Presented is a new analysis framework for removing wave‐bias by accumulation of cross‐power spectral densities below wave frequencies. This analysis framework also includes new measurement guidelines based on wave period, currents, and measurement heights. This framework is applied to sand, seagrass, and reef environments where traditional EC analysis resulted in wave‐bias of 7.0% ± 9.2% error in biogeochemical (oxygen and H+) fluxes, while more variable and higher error was evident in momentum fluxes (10.5% ± 21.0% error). It is anticipated that this framework will lead to significant changes in how EC measurements are conducted and evaluated, and help overcome the major limitations caused by wave‐sensitive and slow‐response sensors, potentially expanding new chemical tracer applications and more widespread use of the EC technique.This work was supported by the Independent Research & Development Program at WHOI grant 25307and NSF OCE grants 1657727 and 1633951

Optimization and Demonstration of In Situ Chemical Sensors for Marine Waters

The importance of autonomous in situ chemical sensors for ocean observations has increased drastically over the last decades. Yet, the huge potentials of sensor-based data collection remain underutilized by the scientific and regulatory communities, despite wider than ever usage of sensors. This thesis is part of a growing body of work to extend the usability of sensors and is embedded in the Ocean Best Practice approach, which could improve data quality in ocean observation in general. The here presented Ph.D. thesis covers multiple commercial sensors (LOC from ClearWater Sensors, Southampton, UK and OPUS from TriOS GmbH, Germany) for autonomous, high-resolution and in situ measurements of essential biogeochemical parameters (pH and nitrate) in marine waters. It was motivated by the necessity of improving the data quality of autonomous submersible optical sensors and broadening their utility. To achieve this, sensor deployments in various aquatic environments were conducted. Furthermore, the data obtained via sensors based on the same analytical principle was compared with each other, and with benchtop laboratory devices to assess the accuracy of the measurements. The achievements are associated with the acquisition of accurate and temporally well-resolved real-time data. A more reliable sensor-based data collection and improved deployability promotes a broader usage of autonomous sensors in general. Thus, a financially more sustainable ocean monitoring approach can be achieved, since a broader adaptation of autonomous sensors in research yields a higher cost efficiency

A BGC-Argo Guide: Planning, Deployment, Data Handling and Usage

The Biogeochemical-Argo program (BGC-Argo) is a new profiling-float-based, ocean wide, and distributed ocean monitoring program which is tightly linked to, and has benefited significantly from, the Argo program. The community has recommended for BGC-Argo to measure six additional properties in addition to pressure, temperature and salinity measured by Argo, to include oxygen, pH, nitrate, downwelling light, chlorophyll fluorescenceandtheopticalbackscatteringcoefficient.Thepurposeofthisadditionisto enable the monitoring of ocean biogeochemistry and health, and in particular, monitor major processes such as ocean deoxygenation, acidification and warming and their effect on phytoplankton, the main source of energy of marine ecosystems. Here we describe the salient issues associated with the operation of the BGC-Argo network, with information useful for those interested in deploying floats and using the data they produce. The topics include float testing, deployment and increasingly, recovery. Aspects of data management, processing and quality control are covered as well as specific issues associated with each of the six BGC-Argo sensors. In particular, it is recommended that water samples be collected during float deployment to be used for validation of sensor output

Analysis of relevant technical issues and deficiencies of the existing sensors and related initiatives currently set and working in marine environment. New generation technologies for cost-effective sensors

The last decade has seen significant growth in the field of sensor networks, which are currently collecting large amounts of environmental data. This data needs to be collected, processed, stored and made available for analysis and interpretation in a manner which is meaningful and accessible to end users and stakeholders with a range of requirements, including government agencies, environmental agencies, the research community, industry users and the public. The COMMONSENSE project aims to develop and provide cost-effective, multi-functional innovative sensors to perform reliable in-situ measurements in the marine environment. The sensors will be easily usable across several platforms, and will focus on key parameters including eutrophication, heavy metal contaminants, marine litter (microplastics) and underwater noise descriptors of the MSFD. The aims of Tasks 2.1 and 2.2 which comprise the work of this deliverable are: • To obtain a comprehensive understanding and an up-to-date state of the art of existing sensors. • To provide a working basis on “new generation” technologies in order to develop cost-effective sensors suitable for large-scale production. This deliverable will consist of an analysis of state-of-the-art solutions for the different sensors and data platforms related with COMMONSENSE project. An analysis of relevant technical issues and deficiencies of existing sensors and related initiatives currently set and working in marine environment will be performed. Existing solutions will be studied to determine the main limitations to be considered during novel sensor developments in further WP’s. Objectives & Rationale The objectives of deliverable 2.1 are: • To create a solid and robust basis for finding cheaper and innovative ways of gathering data. This is preparatory for the activities in other WPs: for WP4 (Transversal Sensor development and Sensor Integration), for WP(5-8) (Novel Sensors) to develop cost-effective sensors suitable for large-scale production, reducing costs of data collection (compared to commercially available sensors), increasing data access availability for WP9 (Field testing) when the deployment of new sensors will be drawn and then realized