Prediction of moisture content of alfalfa using density-independent functions of microwave dielectric properties

Shrestha, Bijay; Wood, H.C.; Sokhansanj, Shahab

doi:10.1088/0957-0233/16/5/018

Cited by 14 publications

(10 citation statements)

References 14 publications

(16 reference statements)

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“…Additionally, Ulaby and El‐Rayes (1987) found that the bound water content increases with decreasing total water content. A number of authors developed mixing models for specific purposes or vegetation compartments, such as the dielectric model for leaves as proposed by Mätzler (1994), and for various plants, such as Shrestha et al (2005, 2007).…”

Section: Canopy Dielectric and Plant Water Propertiesmentioning

confidence: 99%

Characterization of Crop Canopies and Water Stress Related Phenomena using Microwave Remote Sensing Methods: A Review

Vereecken

Weihermüller

Jonard

et al. 2012

Vadose Zone Journal

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In this paper we reviewed the use of microwave remote sensing methods for characterizing crop canopies and vegetation water stress related phenomena. Our analysis includes both active and passive systems that are ground‐based, airborne, or spaceborne. Most of the published results that have examined crop canopy characterization and water stress have used active microwave systems. In general, quantifying the effect of dynamic vegetation properties, and water stress related processes in particular, on the measured microwave signals can still benefit from improved models and more observational data. Integrated data sets providing information on both soil status and plant status are lacking, which has hampered the development and validation of mathematical models. There is a need to link three‐dimensional functional, structural crop models with radiative transfer models to better understand the effect of environmental and related physiological processes on microwave signals and to better quantify the impact of water stress on microwave signals. Such modeling approaches should incorporate both passive and active microwave methods. Studies that combine different sensor technologies that cover the full spectral range from optical to microwave have the potential to move forward our knowledge of the status of crop canopies and particularly water related stress phenomena. Assimilation of remotely sensed properties, such as backscattering coefficient or brightness temperature, in terms of estimating biophysical crop properties using mathematical models is also an unexplored avenue.

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Section: Canopy Dielectric and Plant Water Propertiesmentioning

confidence: 99%

Characterization of Crop Canopies and Water Stress Related Phenomena using Microwave Remote Sensing Methods: A Review

Vereecken

Weihermüller

Jonard

et al. 2012

Vadose Zone Journal

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“…Research studies were also published dealing with the prediction of moisture content based on microwave dielectric spectroscopy for several food items, including alfalfa [ 35 ], onions [ 36 ], dry cured ham [ 28 ], chicken and scallops [ 33 ], among others. Taking into account that the reflected TDR data were correlated with the moisture content of octopus, a calibration of this methodology was further performed to allow a rapid and accurate quantitation of moisture content in O. vulgaris .…”

Section: Resultsmentioning

confidence: 99%

“…The moisture content can be estimated by the following equation: Moisture content (g/100 g) = −0.503 × PC1 + 1.602 × PC2 + 85. 35 The root mean squared error (RMSE) between the reference moisture content (obtained with the destructive method) and the moisture content predicted by the principal component regression calibration was 1.1%, and the coefficient of determination R 2 was 0.784 (p < 0.05).…”

Section: Quantitation Of Moisture Content Of Octopusmentioning

confidence: 95%

Quantitation of Water Addition in Octopus Using Time Domain Reflectometry (TDR): Development of a Rapid and Non-Destructive Food Analysis Method

Teixeira

Vieira

Martins

et al. 2022

Foods

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A rapid and non-destructive method based in time domain reflectometry analysis (TDR), which detects and quantifies the water content in the muscle, was developed for the control of abusive water addition to octopus. Common octopus samples were immersed in freshwater for different periods (0.5–32 h) to give a wide range of moisture contents, representing different commercial conditions. Control and water-added octopus were analyzed with a TDR sensor, and data correlated with moisture content were used for calibration and method validation. A maximum limit of moisture content of 85.2 g/100 g in octopus is proposed for conformity assessment, unless the label indicates that water (>5%) was added. Calibration results showed that TDR analysis can discriminate control and water-added octopus, especially for octopus immersed for longer periods (32 h). In addition, moisture content can be quantified in octopus using only TDR analysis (between 80 and 90 g/100 g; RMSE = 1.1%). TDR data and correlation with moisture content show that this non-destructive methodology can be used by the industry and quality control inspections for assessment of octopus quality and to verify compliance with legislation, promoting fair trade practices, and further contributing to a sustainable use of resources.

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“…On many events empirical per se calibration rules need to be applied to a class of specific materials [516][517][518][519][520], aiming, of course, at a unified description of an as broad as possible variety of species within such class [521,522]. In this context, particular interest is directed toward density-independent relations [522][523][524][525][526]…”

Section: Mixture Relationsmentioning

confidence: 99%

Electromagnetic moisture measurement

Hübner¹,

Kaatze²

2016

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XII which we believe to be useful when considering the design of special sensors and appropriate measurement techniques for moisture determination. A chapter dealing with the dielectric properties of water in its different states of interaction is also included. It is intended to provide information concerning the adequate modelling of data derived from the electromagnetic signals when affected by moist materials. Selected applications are discussed in order to introduce some proven examples of electromagnetic moisture sensors and related measurement methods. Finally, a collection of dielectric data for liquids is presented which may serve as reference in calibration procedures. Preferably data obtained from calibration-free methods is given. Additionally, most of it has been measured at different laboratories and the different series of data agree within the limits of experimental uncertainty. A detailed bibliography is provided in order to assist with further reading. We are indebted to Alexander Brandelik, Karlsruhe, who spent much time to critically read the manuscript before publication. We thank Alexander Schaub, Mannheim, for valuable help with editing the book, including proofreading and formatting.

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Prediction of moisture content of alfalfa using density-independent functions of microwave dielectric properties

Cited by 14 publications

References 14 publications

Characterization of Crop Canopies and Water Stress Related Phenomena using Microwave Remote Sensing Methods: A Review

Characterization of Crop Canopies and Water Stress Related Phenomena using Microwave Remote Sensing Methods: A Review

Quantitation of Water Addition in Octopus Using Time Domain Reflectometry (TDR): Development of a Rapid and Non-Destructive Food Analysis Method

Electromagnetic moisture measurement

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