Article Summaries

High Throughput Phenotyping of Tomato Spot Wilt Disease in Peanuts Using Unmanned Aerial Systems and Multispectral Imaging

Aaron Patrick, Sara Pelham, Albert Culbreath, C. Corely Holbrook,
Ignácio José de Godoy, and Changying Li

The amount of visible and near infrared light reflected by plants varies depending on their health. In this study, multispectral images were acquired by a quadcopter for high throughput phenotyping of tomato spot wilt disease resistance among twenty genotypes of peanuts. The plants were visually assessed to acquire ground truth ratings of disease incidence. Multispectral images were processed into several vegetation indices. Ultimately, the best vegetation indices and pixel distribution feature for disease detection were determined and correlated with manual ratings and yield. The relative resistance of each genotype was then compared. Image-based disease ratings effectively ranked genotype resistance as early as 93 days from seeding.

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Onion Postharvest Quality Assessment with X-Ray Computed Tomography – A Pilot Study

Richard A. Speir and Mark A. Haidekker

Onions are susceptible to bacterial and fungal infections, most critically during the short harvest period from April to May. To allow for a year-round supply, onions are stored in controlled atmosphere facilities. Infected onions, even if no decay or damage is visible, put the entire harvest in the storage facility at risk. Early detection of bacterial and fungal infections is therefore highly desirable. In this pilot study, the authors used a low-cost, custom-built x-ray computed tomography (CT) scanner to obtain cross-sectional images of yellow sweet Granex onions (Allium cepa) that were inoculated with pathogens. CT images were analyzed for features that could potentially be used to detect signs of pathogen-related decay in the early stages of infection. The long-term vision is to use CT scanners in an onion packinghouse to perform automated postharvest quality assessment.

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Remote Estimation of Intra-Parcel Grape Quantity from Three-Dimensional Imagery Technique Using Ground-Based Microwave FMCW Radar


Dominique Henry, Hervé Aubert, Thierry Véronèse, and Éric Serrano

For better benefits and yields, a good estimation of the quantity of grapes in a vineyard is necessary. In this paper, a three-dimensional (3D) imagery technique using conventional 24 GHz frequency-modulated continuous- wave (FMCW) radar is applied for detecting and remotely estimating the intra-parcel quantity of grapes. The microwave sensing is performed from the radar beam scanning of a vineyard, and an estimator is defined to derive the quantity of grapes in grapevines from the radar echoes distribution in the interrogated 3D scene. An algorithm based on contour detection is applied to the 3D radar image and a new parameter, called the spread factor, is defined for classifying the echo levels of grapes. The quantity of grapes is finally deduced from an appropriate estimator. This remote sensing approach brings a new and flexible solution for precision viticulture by estimating the grape quantity even for grapes hidden by leaves.

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TDR Application for Moisture Content
Estimation in Agri-Food Materials


Andrea Cataldo, Egidio De Benedetto, Christof Huebner, and Dennis Trebbels
Cereals and legumes are invaluable resources, as they represent the raw materials of many foods and beverages. Cereals are also largely used as livestock feeds, thus indirectly influencing the quality of dairy products and meat. Because of their key role in human nutrition and well-being, the safety and quality of these agri-food materials are extremely important topics in food science. In this regard, moisture content is one of the ultimate factors influencing the quality, safety and price of the final food product; hence, it is crucial to monitor water content of materials in the food production line. Starting from these considerations, this paper describes the use of time domain reflectometry (TDR) for both in-line and off-line moisture content sensing of agri-food materials. In particular, after a brief description of the basic principles of TDR, two representative application cases for moisture content measurements of agri-food materials are reported and commented on.

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Recent Developments in Stored Grain Sensors, Monitoring and Management Technology


Chandra B. Singh and John M. Fielke

Up to one third of the total annual global production of grain (cereals, oil seeds, and pulses) is lost primarily due to poor post-harvest management. Lack of control over grain moisture content, temperature and insect infestations are the three most significant factors causing this loss. Recent technological advancements in grain storage condition monitoring and control are now helping to safely store grain for periods of several years with minimal quality loss. Grain moisture content and temperature are controlled by installing multiple temperature and humidity sensors in the grain that are used to automate drying and aeration fans. Storage headspace condition monitoring and exhaust fan operation are used to avoid condensation forming in the storage facility. CO2 and insect trap monitoring are used to detect growth in insect numbers and indicate if a control treatment is needed. Fumigant concentration monitoring is used to ensure a lethal dose of insecticide or controlled atmosphere is applied for the required time to the grain.  Only with this suite of sensors and controls can large volumes of grain be monitored and controlled to provide economic safe storage of bulk grain and thus provide an increase in the amount of grain available for consumption.

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Microwave Permittivity-Assisted Artificial Neural Networks for Determining Moisture Content of
Chopped Alfalfa Forage


Bijay L. Shrestha, Hugh C. Wood, Lope Tabil, Oon-Doo Baik, and Shahab Sokhansanj

Moisture content of a commercially important forage biomass such as alfalfa (Madicago sativa), is essential at various stages of production including harvesting, baling, storing, pelleting, and cubing. In this study, the dielectric constants and the dielectric loss factors of chopped alfalfa were measured with an open ended coaxial probe with 20 inputs for artificial neural networks. A three-layer neural network with 20 inputs, five hidden nodes, and one output for moisture content was built on an error back-propagation algorithm with momentum and adaptive learning techniques to predict the moisture content of alfalfa. The prediction of moisture content of alfalfa independent of bulk density in 12 seconds exhibited the potential of this technique in measuring the moisture content of alfalfa and other medicinal and cash crops in batch and in production moisture measurements.
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Blood Oxygenation Measurement by Smartphone


Domenico Luca Carnì, Domenico Grimaldi, Alfonso Nastro,
Vitaliano Spagnuolo, and Francesco Lamonaca

An important evaluation index is arterial blood oxygenation (SO2%), defined as the percentage ratio of the concentration of oxygen-saturated hemoglobin to the total amount of hemoglobin.
Normal values of blood oxygenation are in the range 95-100%. The blood oxygenation values are usually obtained by gas chromatography or use of a pulse oximeter. Both of these techniques have negative characteristics for the patient. This paper presents a comparative analysis of a proposed smartphone application for home use and self-monitoring as a valid alternative to the pulse oximeter and gas chromatograph and provides an emphasis on the accuracy of the experimental results.

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Basic Metrology


 How to Measure a Lobster or Size an Egg
Richard Davis
There are measurements in daily life where only certain points along a continuum need to be precisely known. Purchasing the least-expansive postage stamp for a letter has been a traditional example. In France (where I live), I can save a little money if I can be sure that my letter weighs less than 20 g. The post office does not care to know how much under 20 g. This type of less-than/greater-than measurement also turns out to be important when catching lobsters or selling hen eggs.

This summary was written by the author.

Future Trends in I&M


Synchronized Measurement Technology: A Blessing for Power Systems
Markos Asprou

The advent of phasor measurement units (PMU) has brought a new era in the field of power system monitoring and has defined the future trend of applications that the power-system control center will accommodate. Measuring features such as the fast reporting rate (50-100 measurements/s), synchronization of measurements through GPS signals, measurements of frequency and frequency rate of change, and the provision of phase measurements (instead of only magnitude measurements) were enough to set the synchronized measurement technology (SMT) and consequently the PMU as the key enablers for the real-time monitoring of power systems. In this column, the author discusses how he “strongly believes that SMT is a blessing for power systems. It expands the capabilities and the flexibility of the power system operators to react promptly in emergency situations, and it increases the reliability and security of the power systems. These are very important characteristics for such a critical infrastructure as the electricity network. In the future, power systems are expected to experience unprecedented changes in structure and operation, and I believe that SMT will be a part of those important changes.”

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ATI Industrial Automation


Trimble Navigation Limited

Astronics Test Systems

Marvin Test Systems


Omega Engineering, Inc.

Virginia Panel Corporation


Astronics DME Corportation

Pickering Interfaces Inc.

RADX Technologies, Inc.

Zurich Instruments AG

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