Empirical Calibration Method Research Articles

Uncrewed aerial vehicle radiometric calibration: A comparison of autoexposure and fixed‐exposure images

AbstractRemote sensing with uncrewed aerial vehicles (UAVs) is increasingly being used in agriculture to provide data on the physical characteristics of plants under field conditions. Data accuracy is critical for decision making with a high degree of confidence. In this work, we compared two multispectral camera calibration methods for image data collected with a UAV: (1) an autoexposure method that relies on a single calibration panel and a post hoc calibration, and (2) a fixed‐exposure system that uses three in‐field gray calibration panels using the empirical line calibration method. Both methods were compared to reflectance data from (a) four ground calibration targets measured with a spectroradiometer and (b) a single manned aircraft image calibrated with commercial calibration tarps. In a band‐by‐band comparison, the autoexposure method produced almost twice as much radiometric error on average compared with fixed exposure. Because remote sensing data are commonly converted to spectral indices, the calibration methods were also evaluated by calculating the visible atmospherically resistant index (VARI) and comparing the resulting data to the manned aircraft image. Similarly, the autoexposure method in this case produced twice the error of the fixed‐exposure method. The effect of the error was considered in a production agriculture context by simulating a remote sensing‐based prescription map for pesticide application in a cotton (Gossypium) field and calculating the number of mislabeled management zones. The simulation showed that the autoexposure method would be more costly to the farm because of its higher error, roughly $8.00/ha based on the assumptions made.

Research on accuracy of material identification based on photon counting spectral CT.

Photon counting spectral CT is a significant direction in the development of CT technology and material identification is an important application of spectral CT. However, spectrum estimation in photon counting spectral CT is highly complex and may affect quantification accuracy of material identification. To address the problem of energy spectrum estimation in photon-counting spectral CT, this study investigates empirical material decomposition algorithms to achieve accurate quantitative decomposition of the effective atomic number. The spectrum is first calibrated using the empirical dual-energy calibration (EDEC) method and the effective atomic number is then quantitatively estimated based on the EDEC method. The accuracy of estimating the effective atomic number of materials under different calibration conditions is investigated by designing different calibration phantoms, and accurate quantitation is achieved using suitable calibration settings. Last, the validity of this method is verified through simulations and experimental studies. The results demonstrate that the error in estimating the effective atomic number is reduced to within 4% for low and medium Z materials, thereby enabling accurate material identification. The empirical dual-energy correction method can solve the problem of energy spectrum estimation in photon counting spectral CT. Accurate effective atomic number estimation can be achieved with suitable calibration.

Empirical optimization of energy bin weights for compressing measurements with realistic photon counting x-ray detectors.

Photon counting detectors (PCDs) provide higher spatial resolution, improved contrast-to-noise ratio (CNR), and energy discriminating capabilities. However, the greatly increased amount of projection data in photon counting computed tomography (PCCT) systems becomes challenging to transmit through the slip ring, process, and store. This study proposes and evaluates an empirical optimization algorithm to obtain optimal energy weights for energy bin data compression. This algorithm is universally applicable to spectral imaging tasks including 2 and 3 material decomposition (MD) tasks and virtual monoenergetic images (VMIs). This method is simple to implement while preserving spectral information for the full range of object thicknesses and is applicable to different PCDs, for example, silicon detectors and CdTe detectors. We used realistic detector energy response models to simulate the spectral response of different PCDs and an empirical calibration method to fit a semi-empirical forward model for each PCD. We numerically optimized the optimal energy weights by minimizing the average relative Cramér-Rao lower bound (CRLB) due to the energy-weighted bin compression, for MD and VMI tasks over a range of material area density (0-40g/cm2 water, 0-2.16g/cm2 calcium). We used Monte Carlo simulation of a step wedge phantom and an anthropomorphic head phantom to evaluate the performance of this energy bin compression method in the projection domain and image domain, respectively. The results show that for 2 MD, the energy bin compression method can reduce PCCT data size by 75% and 60%, with an average variance penalty of less than 17% and 3% for silicon and CdTe detectors, respectively. For 3 MD tasks with a K-edge material (iodine), this method can reduce the data size by 62.5% and 40% with an average variance penalty of less than 12% and 13% for silicon and CdTe detectors, respectively. We proposed an energy bin compression method that is broadly applicable to different PCCT systems and object sizes, with high data compression ratio and little loss of spectral information.

Machine Learning-Based Approaches for Predicting SPAD Values of Maize Using Multi-Spectral Images

Precisely monitoring the growth condition and nutritional status of maize is crucial for optimizing agronomic management and improving agricultural production. Multi-spectral sensors are widely applied in ecological and agricultural domains. However, the images collected under varying weather conditions on multiple days show a lack of data consistency. In this study, the Mini MCA 6 Camera from UAV platform was used to collect images covering different growth stages of maize. The empirical line calibration method was applied to establish generic equations for radiometric calibration. The coefficient of determination (R2) of the reflectance from calibrated images and ASD Handheld-2 ranged from 0.964 to 0.988 (calibration), and from 0.874 to 0.927 (validation), respectively. Similarly, the root mean square errors (RMSE) were 0.110, 0.089, and 0.102% for validation using data of 5 August, 21 September, and both days in 2019, respectively. The soil and plant analyzer development (SPAD) values were measured and applied to build the linear regression relationships with spectral and textural indices of different growth stages. The Stepwise regression model (SRM) was applied to identify the optimal combination of spectral and textural indices for estimating SPAD values. The support vector machine (SVM) and random forest (RF) models were independently applied for estimating SPAD values based on the optimal combinations. SVM performed better than RF in estimating SPAD values with R2 (0.81) and RMSE (0.14), respectively. This study contributed to the retrieval of SPAD values based on both spectral and textural indices extracted from multi-spectral images using machine learning methods.

Dosimetric and mechanical equivalency of Varian TrueBeam linear accelerators.

PurposeTo investigate and improve the level of equivalency of Varian TrueBeam linear accelerators (linacs) in energy‐, dosimetric leaf gap‐ (DLG) and jaw calibration.MethodsEight linacs with four photon energies: 6 MV, 6 MV FFF, 10 MV FFF, and 15 MV, and three electron energies (on two linacs): 6, 9, and 12 MeV were commisioned and beam‐matched. Initially, symmetry of lateral profiles was calibrated for maximum field size. Energy‐matching was then performed for photons by adjusting diagonal profiles at maximum field size and depth of maximum dose to coincide with the reference linac, and for electrons by matching the range at percentage depth of ionization of 90%, 80%, and 50%. Calibration of DLG was performed for 6 MV and evaluated among the linacs. The relationship between DLG and the Gap value was investigated. A method using electronic portal imaging device (EPID) was developed and implemented for jaw calibration.ResultsSymmetry calibration for photons (electrons) was within 1% (0.7%), further improving the vendor's acceptance criteria. Photon and electron energy‐matching was within 0.5% and 0.1 mm, respectively. Calibration of DLG was within 0.032 mm among the linacs and utilizing the relationship between DLG and the Gap value resulted in an empirical calibration method which was implemented to simplify DLG adjustment. Using EPID‐based method of calibration, evaluation of the jaw‐positioning among the linacs for 30 cm × 30 cm field size was within 0.4 mm and in the junction area within 0.2 mm. Dose delivery error of VMAT‐plans were at least 99.2% gamma pass rate (1%, 1 mm).ConclusionsHigh level of equivalency, beyond clinically accepted criteria, of TrueBeam linacs could be achieved which reduced dose delivery systematic errors and increased confidence in interchanging patients among linacs.

A simple model for PIFs extraction at digital change detection approach

The radiometric normalization using pseudo-invariant features (PIFs) is one of the best methods of image-based atmospheric correction. However, one of the main challenges of this approach is the correct selection of PIFs. So far many efforts have been made to automate radiometric correction using PIFs, although the capability of all these automated methods has been proven in various studies, their application requires intermediate to advanced statistical and computational knowledge and their application is beyond the reach of most conventional remote sensing users. Therefore, in this research, a straightforward simple method is proposed based on the definition of PIFs that automatically identifies these areas and uses them on a regression procedure for automatic normalization. The study area is Hara Protection Area (the Hara international wetland), which has sub-tropical climate and due to surface homogeneity of its mangrove forests can be used as a pilot for natural, and homogeneous ecosystems such as forested areas. To create an automatic PIFs extraction in this area, initially, we masked areas that should not be in the PIFs by applying some thresholds. At this stage, water, vegetation and mountainous areas were filtered. Then, the radiometric resolution of the two different sensor images was identical, and using the differential histogram shape of the two images, unvaried areas were extracted. To validate the accuracy of the proposed method, absolute radiometric correction using atmospheric and topographic correction (ATCOR), fast line-of-sight atmospheric analysis of hypercubes (FLAASH) and atmospheric correction (ATMOSC) methods, and relative radiometric correction using both empirical line calibration method and dark object subtraction method and automatic radiometric correction using QUick atmospheric correction (QUAC) and autonomous atmospheric correction (IMAGINE AAIC) were applied on the data. The output of all atmospheric correction methods and the proposed method was applied in the image algebra change detection in the form of a difference and with a threshold of twice the standard deviation from the mean to be checked by 219 points. The results of validation and qualitative studies of the histogram comparisons proved the proper functioning of the proposed method (κ greater than 0.8), and using cross tables, the performance of the proposed method is similar to that of the empirical line calibration method (more than 76%). Finally, a few unique features in the current research proposal, including simplicity, automation, negligible systematic error, the possibility of using in a biomarker degradation warning system, the independence on the type of sensor used, distinguish it from other radiometric correction methods.

Effective noise reduction algorithm for material decomposition in dual-energy X-ray inspection

Dual-energy X-ray inspection can provide material-decomposed transmission information of the imaged object enhancing observer’s inspection performance. The material decomposition algorithms have an inherent noise amplification problem due to the multiplication and division operations during dual-energy image processing, which often degrades the material decomposition performance. In this work, we propose an effective and reliable clustering algorithm to resolve the noise amplification problem. The proposed method utilizes a k-means cluster algorithm as a base method with Gaussian noise of the data considered. In addition, we added a probabilistic regularization that can effectively relieve the decision challenge of the initial number of clusters. We have applied the proposed denoising method to the prototype X-ray dual-energy inspection system with an empirical calibration method that we have previously proposed. The proposed algorithm showed substantial reduction of noise in the test container projections and accordingly improved the material decomposition accuracy. Moreover, we performed quantitative analysis of the empirical calibration method with and without the cluster-based noise reduction algorithm and also on the conventional calibration method for material decomposition. It showed that the empirical calibration method with the noise reduction algorithm is robust against the thickness variation of the target object. The results suggest that the proposed noise reduction algorithm with the empirical calibration method is a promising solution to dual-energy X-ray material decomposition for inspection.

The Interstellar Medium in [O iii]-selected Star-forming Galaxies at z ∼ 3.2

Abstract We present new results from near-infrared spectroscopy with Keck/MOSFIRE of [O iii]-selected galaxies at z ∼ 3.2 . With our H and K band spectra, we investigate the interstellar medium (ISM) conditions, such as ionization states and gas metallicities. [O iii] emitters at z ∼ 3.2 show a typical gas metallicity of 12 + log ( O / H ) = 8.07 ± 0.07 at log ( M * / M ⊙ ) ∼ 9.0 – 9.2 and 12 + log ( O / H ) = 8.31 ± 0.04 at log ( M * / M ⊙ ) ∼ 9.7 – 10.2 when using the empirical calibration method. We compare the [O iii] emitters at z ∼ 3.2 with UV-selected galaxies and Lyα emitters at the same epoch and find that the [O iii]-based selection does not appear to show any systematic bias in the selection of star-forming galaxies. Moreover, comparing with star-forming galaxies at z ∼ 2 from the literature, our samples show similar ionization parameters and gas metallicities as those obtained by the previous studies that used the same calibration method. We find no strong redshift evolution in the ISM conditions between z ∼ 3.2 and z ∼ 2 . Considering that the star formation rates at a fixed stellar mass also do not significantly change between the two epochs, our results support the idea that the stellar mass is the primary quantity to describe the evolutionary stages of individual galaxies at z > 2 .

Novel minimal physiologically-based model for the prediction of passive tubular reabsorption and renal excretion clearance

PurposeDevelop a minimal mechanistic model based on in vitro–in vivo extrapolation (IVIVE) principles to predict extent of passive tubular reabsorption. Assess the ability of the model developed to predict extent of passive tubular reabsorption (Freab) and renal excretion clearance (CLR) from in vitro permeability data and tubular physiological parameters. MethodsModel system parameters were informed by physiological data collated following extensive literature analysis. A database of clinical CLR was collated for 157 drugs. A subset of 45 drugs was selected for model validation; for those, Caco-2 permeability (Papp) data were measured under pH6.5–7.4 gradient conditions and used to predict Freab and subsequently CLR. An empirical calibration approach was proposed to account for the effect of inter-assay/laboratory variation in Papp on the IVIVE of Freab. ResultsThe 5-compartmental model accounted for regional differences in tubular surface area and flow rates and successfully predicted the extent of tubular reabsorption of 45 drugs for which filtration and reabsorption were contributing to renal excretion. Subsequently, predicted CLR was within 3-fold of the observed values for 87% of drugs in this dataset, with an overall gmfe of 1.96. Consideration of the empirical calibration method improved overall prediction of CLR (gmfe=1.73 for 34 drugs in the internal validation dataset), in particular for basic drugs and drugs with low extent of tubular reabsorption. ConclusionsThe novel 5-compartment model represents an important addition to the IVIVE toolbox for physiologically-based prediction of renal tubular reabsorption and CLR. Physiological basis of the model proposed allows its application in future mechanistic kidney models in preclinical species and human.

Simple and accurate empirical absolute volume calibration of a multi-sensor fringe projection system

This paper suggests a novel absolute empirical calibration method for a multi-sensor fringe projection system. The optical setup of the projector-camera sensor can be arbitrary. The term absolute calibration here means that the centre of the three dimensional coordinates in the resultant calibrated volume coincides with a preset centre to the three-dimensional real-world coordinate system. The use of a zero-phase fringe marking spot is proposed to increase depth calibration accuracy, where the spot centre is determined with sub-pixel accuracy. Also, a new method is proposed for transversal calibration. Depth and transversal calibration methods have been tested using both single sensor and three-sensor fringe projection systems. The standard deviation of the error produced by this system is 0.25mm. The calibrated volume produced by this method is 400mm×400mm×140mm.

Evaluation of an empirical monitor output estimation in carbon ion radiotherapy

A conventional broad beam method is applied to carbon ion radiotherapy at Gunma University Heavy Ion Medical Center. According to this method, accelerated carbon ions are scattered by various beam line devices to form 3D dose distribution. The physical dose per monitor unit (d/MU) at the isocenter, therefore, depends on beam line parameters and should be calibrated by a measurement in clinical practice. This study aims to develop a calculation algorithm for d/MU using beam line parameters. Two major factors, the range shifter dependence and the field aperture effect, are measured via PinPoint chamber in a water phantom, which is an identical setup as that used for monitor calibration in clinical practice. An empirical monitor calibration method based on measurement results is developed using a simple algorithm utilizing a linear function and a double Gaussian pencil beam distribution to express the range shifter dependence and the field aperture effect. The range shifter dependence and the field aperture effect are evaluated to have errors of 0.2% and 0.5%, respectively. The proposed method has successfully estimated d/MU with a difference of less than 1% with respect to the measurement results. Taking the measurement deviation of about 0.3% into account, this result is sufficiently accurate for clinical applications. An empirical procedure to estimate d/MU with a simple algorithm is established in this research. This procedure allows them to use the beam time for more treatments, quality assurances, and other research endeavors.

SU-E-I-38: Improved Metal Artifact Correction Using Adaptive Dual Energy Calibration

Purpose: The empirical dual energy calibration (EDEC) method corrects for beam-hardening artifacts, but shows limited performance on metal artifact correction. In this work, we propose an adaptive dual energy calibration (ADEC) method to correct for metal artifacts. Methods: The empirical dual energy calibration (EDEC) method corrects for beam-hardening artifacts, but shows limited performance on metal artifact correction. In this work, we propose an adaptive dual energy calibration (ADEC) method to correct for metal artifacts. Results: Highly attenuating copper rods cause severe streaking artifacts on standard CT images. EDEC improves the image quality, but cannot eliminate the streaking artifacts. Compared to EDEC, the proposed ADEC method further reduces the streaking resulting from metallic inserts and beam-hardening effects and obtains material decomposition images with significantly improved accuracy. Conclusion: We propose an adaptive dual energy calibration method to correct for metal artifacts. ADEC is evaluated with the Shepp-Logan phantom, and shows superior metal artifact correction performance. In the future, we will further evaluate the performance of the proposed method with phantom and patient data.

Aerosol filter analysis using polarized optics EDXRF with thin-film FP method

Interest in atmospheric aerosol issues has been increasing worldwide. X-ray fluorescence (XRF) is an important atmospheric aerosol monitoring tool for inorganic component analysis, because XRF is a rapid and easy analysis method. In particular, Energy dispersive X-ray fluorescence (EDXRF) has drawn attention for aerosol analysis. However, EDXRF has difficulties that: (1) many overlapping peaks exist for aerosol filter analysis and (2) many thin-film standard samples are required when an empirical calibration method is employed. Accurate analysis method of aerosol filter samples without the need for large sets of standards by semi-quantitative analysis software RPF–SQX (Rigaku profile fitting–spectra quant X), which includes the exact profile fitting and thin-film fundamental parameter (FP) method, is described using the EDXRF spectrometer equipped with secondary targets and polarized optics.

Calibration of Temperature Effect on Dielectric Probes Using Time Series Field Data

Dielectric sensors have been widely used for nondestructive determination of volumetric soil water content (θ). Since the output of such sensors is influenced by soil temperature (T), the calibration for the dependence is indispensable for accurate determination of θ. The objectives of this study were (i) to apply an existing empirical temperature calibration method for capacitance probes to other types of commercial dielectric probes and (ii) to propose a new calibration method using time series of field data that requires no laboratory experiments for temperature calibration. Laboratory experiments were performed to obtain probe outputs at various T (5– 35°C) and θ (air dry–near saturation), using two soils and seven probes. From the results, a calibration equation describing the probe output as a function of θ and T was derived for every soil–probe combination and confirmed that this method is applicable not only to capacitance probes but also to impedance and TDR probes. Time series of field data (θ and T) had been previously monitored with ECH2O EC‐5 and EC‐20 capacitance probes in the Loess Plateau, China. Hourly outputs from the probes and T at the 5‐cm depth were analyzed, and calibration equations were derived using the responses of the probe outputs to daily fluctuation of T. The derived calibration equations from the field data were in good agreement with those from laboratory experiment for both probes. The equation was applied to field data and validly removed the effect of T on the probe output.

An empirical calibration method for an a-Si portal imaging device: applications in pretreatment verification of IMRT

A new calibration method for an amorphous silicon (a-Si) electronic portal imaging device (EPID) used for dose measurements in pretreatment verification (field-related) of intensity-modulated radiation therapy (IMRT) with sliding-window technique. The method is independent of data contained in the multileaf collimator (MLC) leaf-motion files and of any calculations made by the treatment planning system (TPS). Sensitivity of the EPID is dependent on radiation energy. For fluence-modulated fields, different dose/reading calibration factors are associated with each pixel of the image acquired by calculating equivalent areas representing the exact ratio between primary and scatter components. The dose measured in the detector plane was compared with that calculated with TPS by using gamma-analysis. Each calibration factor was compared with that calculated by considering the individual contributions of primary and secondary radiation obtained using the convolution method with analytical kernel for homogeneous media. In 837/854 (98%) of the clinical fields analysed, the proportion of irradiated area in which the gamma-index was <1.0 exceeded 95%. The overall average gamma-index was 0.39. There was good agreement between the dose/reading calibration factors obtained with the empirical algorithm and with the convolution method. The proposed calibration method is suitable for routine clinical pretreatment verification in IMRT.

Empirical Models for Radiometric Calibration of Digital Aerial Frame Mosaics

The advent of routine collection of high-quality digital photography provides for traditional uses, as well as “remote sensing” uses such as the monitoring of environmental indicators. A well-devised monitoring system, based on consistent data and methods, provides the opportunity to track and communicate changes in features of interest in a way that has not previously been possible. Data that are geometrically and radiometrically consistent are fundamental to establishing systems for monitoring. In this paper, we focus on models for the radiometric calibration of mosaics consisting of thousands of images. We apply the models to the data acquired by the Australian Commonwealth Scientific and Industrial Research Organisation and its partners as part of regular systematic acquisitions over the city of Perth for a project known as Urban Monitor. One goal of the project, and hence the model development, is to produce annually updated mosaics calibrated to reflectance at 0.2-m ground sample distance for an area of approximately 9600 km2. This equates to terabytes of data and, for frame-based instruments, tens of thousands of images. For the experiments considered in this paper, this requires mosaicking estimates derived from 3000 digital photographic frames, and the methods will shortly be expanded to 30 000+ frames. A key part of the processing is the removal of spectral variation due to the viewing geometry, typically attributed to the bidirectional reflectance distribution function (BRDF) of the land surface. A variety of techniques based on semiempirical BRDF kernels have been proposed in the literature for correcting the BRDF effect in single frames, but mosaics with many frames provide unique challenges. This paper presents and illuminates a complete empirical radiometric calibration method for digital aerial frame mosaics, based on a combined model that uses kernel-based techniques for BRDF correction and incorporates additive and multiplicative terms for correcting other effects, such as variations due to the sensor and atmosphere. Using ground truth, which consists of laboratory-measured white, gray, and black targets that were placed in the field at the time of acquisition, we calculate the fundamental limitations of each model, leading to an optimal result for each model type. We demonstrate estimates of ground reflectance that are accurate to approximately 10%, 5%, and 3% absolute reflectances for ground targets having reflectances of 90%, 40%, and 4%, respectively.

Design and Development of a Multi-Purpose Low-Cost Hyperspectral Imaging System

Hyperspectral image analysis is gaining momentum in a wealth of natural resources and agricultural applications facilitated by the increased availability of low-cost imaging systems. In this study, we demonstrate the development of the Vegetation Mobile Mapping System (VMMS), a low-cost hyperspectral sensing system that is supported by consumer-grade digital camera(s). The system was developed using off-the-shelf imaging and navigation components mainly for ground-based applications. The system integrates a variety of components including timing and positioning GPS receivers and an Inertial Measurement Unit (IMU). The system was designed to be modular and interoperable allowing the imaging components to be used with different navigation systems. The technique used for synchronizing captured images with GPS time was presented. A relative radiometric calibration technique utilizing images of homogeneous targets to normalize pixel gain and offset parameters was used. An empirical spectral calibration method was used to assign wavelengths to image bands. Data acquisition parameters to achieve appropriate spatial coverage were presented. The system was tested in ground-based data collection and analysis experiments that included water quality and vegetation studies.

Calibration and Simultaneous Monitoring of Soil Water Content and Salinity with Capacitance and Four-electrode Probes

Non-destructive monitoring of soil water content (W) and the electrical conductivity of the soil solution (ECw) has been desired for environmental evaluation and sustainable agriculture. Dielectric probes and four-electrode probes are widely used for the non-destructive determination of W and the soil bulk electrical conductivity (ECb), respectively. Since the output of dielectric probes is affected by soil salinity, the calibration for the effect is indispensable for accurate determination of W. Meanwhile, four-electrode probes require the W value for determination of ECw from ECb. We present an empirical calibration method for the salinity dependence of commercial capacitance moisture probes. A four-electrode probe was also calibrated to investigate the possibility of simultaneous monitoring of W and ECw by combining each calibration equation for capacitance and four-electrode probes. A laboratory experiment was conducted using a sandy soil to obtain probe outputs at various W (air-dry-near-saturation) and ECw (0-31.9 dS m-1). The output of the capacitance probe exhibited strong, nonlinear dependence on ECw. The root mean square error (RMSE) between actual W and calculated W using the linear functions provided by the manufacturer was at a maximum of 0.162 m3 m-3. A calibration equation, describing the probe output as a function of W and ECw, was developed using curve fitting approach. The RMSE between the actual and calibrated W by this equation was at a maximum of 0.011 m3 m-3. The output of the four-electrode probe (ECb) was also expressed as a function of W and ECw. The calibration equations for each probe were combined and solved for W and ECw. Although both W and ECw were determined with acceptable accuracy, the combined calibration equation had multiple solutions for W. Development of the method to select optimal solutions will be needed for the practical application of this probe combination.

CANOPY STRUCTURE AND DEPOSITION EFFICIENCY OF VINEYARD SPRAYERS

A field study was performed to analyse how deposition efficiency from an axial-fan sprayer was affected by the canopy structure of vines trained to the High Cordon, Low Cordon and Casarsa systems, at beginning of flowering and beginning of berry touch growth stages. An empirical calibration method, providing a dose rate adjustment roughly proportional to canopy height, was used. The canopy structure was assessed using the Point Quadrat method, and determining the leaf area index (LAI) and the leaf layer index (LLI). Spray deposits were measured by colorimetry, using a water soluble dye (Tartrazine) as a tracer. Correlation between deposits and canopy parameters were analysed and discussed. Foliar deposits per unit leaf area were relatively constant, suggesting that empirical calibration can reduce deposit variability associated with different training systems and growth stages. Total foliar deposition ranged from 33.6% and 82.3% of total spray volume, and increased proportionally with the LLI up to LLI&lt;4. Deposits on bunches significantly decreased with the LLI in the grape zone. The results suggest that sprayer efficiency is improved by a regular, symmetrical canopy, with few leaf layers in the grape zone as in Low Cordon. However, a LLI&lt;3 over the whole canopy and &gt;40% gaps in the foliage both reduced total deposition, and may increase the risk for larger drift losses.

In situ gamma-ray spectrometry for environmental monitoring: a semi empirical calibration method

In situ gamma spectrometry using high-purity germanium (HPGe) detectors is a frequently used method for the determination of radionuclide ground deposition levels. Such measurements do, however, require an efficiency calibration based on detector sensitivity and parameters such as soil density and vertical activity distribution. In this work, a novel expression is used for the detector efficiency, incorporating both the influence of photon energy and incidence angle. Detector-specific efficiency data are determined empirically. For the theoretical calculation of the photon fluence at the detector, a three-layer model of finite thickness is developed for the description of soil density and vertical activity distribution. In order to facilitate the calibration of in situ measurements, a PC program has been developed to enable rapid, on-site calculations of radionuclide ground deposition levels. The semi empirical calibration method was tested on in situ measurements with two different detectors, and the results show good agreement with results obtained from traditional soil sampling.