Display omitted
•HIU is a potential technology for adoption in the dairy industry.•Ultrasound significantly modifies the components in milk.•Ultrasound improves gelation and syneresis during cheese ...production.•The texture of dairy products can be manipulated by ultrasound.•Ultrasound reduces fermentation time or dairy products.•Improvements depend on time, frequency and intensity of sonication.
Alternative methods for improving traditional food processing have increased in the last decades. Additionally, the development of novel dairy products is gaining importance due to an increased consumer demand for palatable, healthy, and minimally processed products. Ultrasonic processing or sonication is a promising alternative technology in the food industry as it has potential to improve the technological and functional properties of milk and dairy products. This review presents a detailed summary of the latest research on the impact of high-intensity ultrasound techniques in dairy processing. It explores the ways in which ultrasound has been employed to enhance milk properties and processes of interest to the dairy industry, such as homogenization, emulsification, yogurt and fermented beverages production, and food safety. Special emphasis has been given to ultrasonic effects on milk components; fermentation and spoilage by microorganisms; and the technological, functional, and sensory properties of dairy foods. Several current and potential applications of ultrasound as a processing technique in milk applications are also discussed in this review.
Interferometric coherence from SAR data is a tool used in a variety of Earth observation applications. In the context of crop monitoring, vegetation indices are commonly used to describe crop ...dynamics. The most frequently used vegetation indices based on radar data are constructed using the backscattered intensity at different polarimetric channels. As coherence is sensitive to the changes in the scene caused by vegetation and its evolution, it may potentially be used as an alternative tool in this context. The objective of this work is to evaluate the potential of using Sentinel-1 interferometric coherence for this purpose. The study area is an agricultural region in Sevilla, Spain, mainly covered by 18 different crops. Time series of different backscatter-based radar vegetation indices and the coherence amplitude for both VV and VH channels from Sentinel-1 were compared to the NDVI derived from Sentinel-2 imagery for a 5-year period, from 2017 to 2021. The correlations between the series were studied both during and outside the growing season of the crops. Additionally, the use of the ratio of the two coherences measured at both polarimetric channels was explored. The results show that the coherence is generally well correlated with the NDVI across all seasons. The ratio between coherences at each channel is a potential alternative to the separate channels when the analysis is not restricted to the growing season of the crop, as its year-long temporal evolution more closely resembles that of the NDVI. Coherence and backscatter can be used as complementary sources of information, as backscatter-based indices describe the evolution of certain crops better than coherence.
This paper deals with the retrieval of agricultural crop height from space by using multipolarization Synthetic Aperture Radar (SAR) images. Coherent and incoherent crop height estimation methods are ...discussed for the first time with a unique TanDEM-X dataset acquired over rice cultivation areas. Indeed, with its polarimetric and interferometric capabilities, the TanDEM-X mission enables the tracking of crop height through interferometric SAR (InSAR), polarimetric interferometric SAR (PolInSAR) and the inversion of radiative transfer-based backscattering model. The paper evaluates the three aforementioned techniques simultaneously with a data set acquired in September 2014 and 2015 over rice fields in Turkey during their reproductive stage. The assessment of the absolute height accuracy and the limitations of the approaches are provided. In-situ measurements conducted in the same cultivation periods are used for validation purposes. The PolInSAR and morphological backscattering model results showed better performance with low RMSEs (12 and 13cm) compared to the differential InSAR result having RMSE of 18cm.
The spatial baseline, i.e. the distance between satellites, is a key parameter for coherent methods such as InSAR and PolInSAR. Its effect on the absolute height accuracy is discussed using TanDEM-X pairs separated by a baseline of 101.7m and 932m. Although the InSAR based approach is demonstrated to provide sufficient crop height accuracy, the availability of a precise vegetation-free digital elevation model and a structurally dense crop are basic requirements for achieving high accuracy. The PolInSAR approach provides reliable crop height estimation if the spatial baseline is large enough for the inversion. The impact of increasing spatial baseline on the absolute accuracy of the crop height estimation is evident for both methods. However, PolInSAR is more cost-efficient, e.g. there is no need for phase unwrapping and any external vegetation free surface elevation data. Instead, the usage of radiative transfer based backscattering models provides not only crop height but also other biophysical properties of the crops with consistent accuracy. The efficient retrieval of crop height with backscattering model is achieved by metamodelling, which makes the computational cost of backscattering inversion comparable to the ones of the coherent methods. However, effectiveness depends on not only the backscattering model, but also the integration of agronomic crop growth rules. Motivated by these results, a combination of backscattering and PolInSAR inversion models would provide a successful method of future precision farming studies.
•Three algorithms were compared for crop height monitoring with a unique dataset.•The first demonstration of crop height retrieval with PolInSAR spaceborne data.•Assessment of relative and absolute height accuracy using InSAR over crops.•RTT demonstrates its superiority when surrogate model is provided.
The feasibility of retrieving the phenological stage of rice fields at a particular date by employing coherent copolar dual-pol X-band radar images acquired by the TerraSAR-X sensor has been ...investigated in this paper. A set of polarimetric observables that can be derived from this data type has been studied by using a time series of images gathered during the whole cultivation period of rice. Among the analyzed parameters, besides backscattering coefficients and ratios, we have observed clear signatures in the correlation (in magnitude and phase) between channels in both the linear and Pauli bases, as well as in parameters provided by target decomposition techniques, like entropy and alpha from the eigenvector decomposition. A new model-based decomposition providing estimates of a random volume component plus a polarized contribution has been proposed and employed in interpreting the radar response of rice. By exploiting the signatures of these observables in terms of the phenology of rice, a simple approach to estimate the phenological stage from a single pass has been devised. This approach has been tested with the available data acquired over a site in Spain, where rice is cultivated, ensuring ground is flooded for the whole cultivation cycle, and sowing is carried out by randomly spreading the seeds on the flooded ground. Results are in good agreement with the available ground measurements despite some limitations that exist due to the reduced swath coverage of the dual-pol HHVV mode and the high noise floor of the TerraSAR-X system.
In this study, we advance a new family of model-based decompositions adapted for dual-pol synthetic aperture radar data. These are formulated using the Stokes vector formalism, coupled to mappings ...from full quad-pol decomposition theory. A generalized model-based decomposition is developed, which allows separation of an arbitrary Stokes vector into partially polarized and polarized wave components. We employ the widely used random dipole cloud as a volume model but, in general, nondipole options can be used. The cross-polarized phase <inline-formula> <tex-math notation="LaTeX">\delta </tex-math></inline-formula>, and the <inline-formula> <tex-math notation="LaTeX">\alpha </tex-math></inline-formula> angle, which is a function of the ratio between wave components, measure the transformation of polarization state on reflection. We apply the decomposition to dual-pol data provided by Sentinel-1 (S1) covering different scenarios, such as agricultural, forest, urban, and glacial land-ice. We show that the polarized term of received polarization state is not usually the same as the transmitted one, and can therefore be used for key applications, e.g., classification and geo-physical parameter estimation. We show that, for vegetated terrain, depolarization is not the only influencing factor to S1 backscattered intensities and, in the case of vertical crops (e.g., rice), this allows the crop orientation effects to be decoupled from volume scattering in the canopy. We demonstrate that coherent dual-pol systems show strong phase signatures over glaciers, where the polarized contribution significantly affects the backscattered state, resulting in elliptical polarization on receive. This is a key result for S1, for which dual-pol phase analysis coupled to dense time series offer great opportunities for land-ice monitoring.
This article investigates and demonstrates the suitability of the Sentinel-1 interferometric coherence for land cover and vegetation mapping. In addition, this study analyzes the performance of this ...feature along with polarization and intensity products according to different classification strategies and algorithms. Seven different classification workflows were evaluated, covering pixel- and object-based analyses, unsupervised and supervised classification, different machine-learning classifiers, and the various effects of distinct input features in the SAR domain-interferometric coherence, backscattered intensities, and polarization. All classifications followed the Corine land cover nomenclature. Three different study areas in Europe were selected during 2015 and 2016 campaigns to maximize diversity of land cover. Overall accuracies (OA), ranging from 70% to 90%, were achieved depending on the study area and methodology, considering between 9 and 15 classes. The best results were achieved in the rather flat area of Doñana wetlands National Park in Spain (OA 90%), but even the challenging alpine terrain around the city of Merano in northern Italy (OA 77%) obtained promising results. The overall potential of Sentinel-1 interferometric coherence for land cover mapping was evaluated as very good. In all cases, coherence-based results provided higher accuracies than intensity-based strategies, considering 12 days of temporal sampling of the Sentinel-1 A stack. Both coherence and intensity prove to be complementary observables, increasing the overall accuracies in a combined strategy. The accuracy is expected to increase when Sentinel-1 A/B stacks, i.e., six-day sampling, are considered.
Sentinel-1 Synthetic Aperture Radar (SAR) data have provided an unprecedented opportunity for crop monitoring due to its high revisit frequency and wide spatial coverage. The dual-pol (VV-VH) ...Sentinel-1 SAR data are being utilized for the European Common Agricultural Policy (CAP) as well as for other national projects, which are providing Sentinel derived information to support crop monitoring networks. Among the Earth observation products identified for agriculture monitoring, indicators of vegetation status are deemed critical by end-user communities. In literature, several experiments usually utilize the backscatter intensities to characterize crops. In this study, we have jointly utilized the scattering information in terms of the degree of polarization and the eigenvalue spectrum to derive a new vegetation index from dual-pol (DpRVI) SAR data. We assess the utility of this index as an indicator of plant growth dynamics for canola, soybean, and wheat, over a test site in Canada. A temporal analysis of DpRVI with crop biophysical variables (viz., Plant Area Index (PAI), Vegetation Water Content (VWC), and dry biomass (DB)) at different phenological stages confirms its trend with plant growth dynamics. For each crop type, the DpRVI is compared with the cross and co-pol ratio (σVH0/σVV0) and dual-pol Radar Vegetation Index (RVI = 4σVH0/(σVV0 + σVH0)), Polarimetric Radar Vegetation Index (PRVI), and the Dual Polarization SAR Vegetation Index (DPSVI). Statistical analysis with biophysical variables shows that the DpRVI outperformed the other four vegetation indices, yielding significant correlations for all three crops. Correlations between DpRVI and biophysical variables are highest for canola, with coefficients of determination (R2) of 0.79 (PAI), 0.82 (VWC), and 0.75 (DB). DpRVI had a moderate correlation (R2≳ 0.6) with the biophysical parameters of wheat and soybean. Good retrieval accuracies of crop biophysical parameters are also observed for all three crops.
•Proposed a new dual-pol radar vegetation index for Sentinel-1.•DpRVI follows the phenological trend with plant growth.•Investigated Dop and eigenvalue spectrum of dual-pol data to map crop condition.•DpRVI outperforms VH/VV and RVI for correlations with biophysical parameters.
The fast growing family of organic-inorganic hybrid compounds has recently been attracting increased attention owing to the remarkable functional properties (magnetic, multiferroic, optoelectronic, ...photovoltaic) displayed by some of its members. Here we show that these compounds can also have great potential in the until now unexplored field of solid-state cooling by presenting giant barocaloric effects near room temperature already under easily accessible pressures in the hybrid perovskite TPrAMn(dca)
(TPrA: tetrapropylammonium, dca: dicyanamide). Moreover, we propose that this will not be an isolated example for such an extraordinary behaviour as many other organic-inorganic hybrids (metal-organic frameworks and coordination polymers) exhibit the basic ingredients to display large caloric effects which can be very sensitive to pressure and other external stimuli. These findings open up new horizons and great opportunities for both organic-inorganic hybrids and for solid-state cooling technologies.
The potential use of the interferometric coherence measured with Sentinel-1 satellites as input feature for crop classification is explored in this study. A one-year time-series of Sentinel-1 images ...acquired over an agricultural area in Spain, in which 17 crop species are present, is exploited for this purpose. Different options regarding temporal baselines, polarization, and combination with radiometric data (backscattering coefficient) are analyzed. Results show that both radiometric and interferometric features provide notable classification accuracy when used individually (overall accuracy lies between 70% and 80%). It is found that the shortest temporal baseline coherences (6 days) and the use of all available intensity images perform best, hence proving the advantage of the 6-day revisit time provided by the Sentinel-1 constellation with respect to longer revisit times. It is also shown that dual-pol data always provide better classification results than single-pol ones. More importantly, when both coherence and backscattering coefficient are jointly used, a significant increase in accuracy is obtained (greater than 7% in overall accuracies). Individual accuracies of all crop types are increased, and an overall accuracy above 86% is reached. This proves that both features provide complementary information, and that the combination of interferometric and radiometric radar data constitutes a solid information source for this application.
A geometrical decorrelation constitutes one of the sources of noise present in Synthetic Aperture Radar (SAR) interferograms. It comes from the different incidence angles of the two images used to ...form the interferograms, which cause a spectral (frequency) shift between them. A geometrical decorrelation must be compensated by a specific filtering technique known as
, the goal of which is to estimate this spectral displacement and retain only the common parts of the images' spectra, reducing the noise and improving the quality of the interferograms. Multiple range filters have been proposed in the literature. The most widely used methods are an
filter approach, which estimates the spectral shift directly from the data; a method based on
information, which assumes a constant-slope (or flat) terrain; and
algorithms, which consider both orbital information and auxiliary topographic data. Their advantages and limitations are analyzed in this manuscript and, additionally, a new, more refined approach is proposed. Its goal is to enhance the filtering process by automatically adapting the filter to all types of surface variations using a multi-scale strategy. A pair of RADARSAT-2 images that mapped the mountainous area around the Etna volcano (Italy) are used for the study. The results show that filtering accuracy is improved with the new method including the steepest areas and vegetation-covered regions in which the performance of the original methods is limited.
PDF
