The Biot-Granier (Gbt) is a new thermal dissipation-based sap flow measurement methodology, comprising sensors, data management and automatic data processing. It relies on the conventional Granier ...(Gcv) methodology upgraded with a modified Granier sensor set, as well as on an algorithm to measure the absolute temperatures in the two observation points and perform the Biot number approach. The work described herein addresses the construction details of the Gbt sensors and the characterization of the overall performance of the Gbt method after comparison with a commercial sap flow sensor and independent data (i.e., volumetric water content, vapor pressure deficit and eddy covariance technique). Its performance was evaluated in three trials: potted olive trees in a greenhouse and two vineyards. The trial with olive trees in a greenhouse showed that the transpiration measures provided by the Gbt sensors showed better agreement with the gravimetric approach, compared to those provided by the Gcv sensors. These tended to overestimate sap flow rates as much as 4 times, while Gbt sensors overestimated gravimetric values 1.5 times. The adjustments based on the Biot equations obtained with Gbt sensors contribute to reduce the overestimates yielded by the conventional approach. On the other hand, the heating capacity of the Gbt sensor provided a minimum of around 7 °C and maximum about 9 °C, contrasting with a minimum around 6 °C and a maximum of 12 °C given by the Gcv sensors. The positioning of the temperature sensor on the tip of the sap flow needle proposed in the Gbt sensors, closer to the sap measurement spot, allow to capture sap induced temperature variations more accurately. This explains the higher resolution and sensitivity of the Gbt sensor. Overall, the alternative Biot approach showed a significant improvement in sap flow estimations, contributing to adjust the Granier sap flow index, a vulnerability of that methodology.
In this work a new algorithm is derived for the onboard calibration of three-axis strapdown magnetometers. The proposed calibration method is written in the sensor frame, and compensates for the ...combined effect of all linear time-invariant distortions, namely soft iron, hard iron, sensor nonorthogonality, and bias, among others. A maximum likelihood estimator (MLE) is formulated to iteratively find the optimal calibration parameters that best fit to the onboard sensor readings, without requiring external attitude references. It is shown that the proposed calibration technique is equivalent to the estimation of a rotation, scaling and translation transformation, and that the sensor alignment matrix is given by the solution of the orthogonal Procrustes problem. Good initial conditions for the iterative algorithm are obtained by a suboptimal batch least squares computation. Simulation and experimental results with low-cost sensors data are presented and discussed, supporting the application of the algorithm to autonomous vehicles and other robotic platforms.
•SIMDualKc and METRIC models were used to estimate olive evapotranspiration (ET).•Ground data, satellite based and dual crop coefficient estimates of ET agreed well.•Modeling results are comparable ...and models complementary in spatial/temporal scales.•Crop coefficients obtained from both models are comparable.•Results provide useful tools to estimate ET in super-high density olive orchards.
The estimation of crop evapotranspiration (ETc) from the reference evapotranspiration (ETo) and a standard crop coefficient (Kc) in olive orchards requires that the latter be adjusted to planting density and height. The use of the dual Kc approach may be the best solution because the basal crop coefficient Kcb represents plant transpiration and the evaporation coefficient reproduces the soil coverage conditions and the frequency of wettings. To support related computations for a super intensive olive orchard, the model SIMDualKc was adopted because it uses the dual Kc approach. Alternatively, to consider the physical characteristics of the vegetation, the satellite-based surface energy balance model METRIC™ – Mapping EvapoTranspiration at high Resolution using Internalized Calibration – was used to estimate ETc and to derive crop coefficients. Both approaches were compared in this study. SIMDualKc model was calibrated and validated using sap-flow measurements of the transpiration for 2011 and 2012. In addition, eddy covariance estimation of ETc was also used. In the current study, METRIC™ was applied to Landsat images from 2011 to 2012. Adaptations for incomplete cover woody crops were required to parameterize METRIC. It was observed that ETc obtained from both approaches was similar and that crop coefficients derived from both models showed similar patterns throughout the year. Although the two models use distinct approaches, their results are comparable and they are complementary in spatial and temporal scales.
This paper presents a new ultrashort baseline (USBL) tightly coupled integration technique to enhance error estimation in low‐cost strapdown inertial navigation systems (INSs), with application to ...underwater vehicles. In the proposed strategy, the acoustic array spatial information is directly exploited in an extended Kalman filter (EKF) implemented in a direct feedback structure. Instead of using the USBL position fixes or computed range and elevation/bearing angles to correct the INS error drifts, as in classical loosely coupled strategies, the novel tightly coupled strategy directly embeds in the EKF the round‐trip‐time and time‐difference‐of‐arrival of the acoustic signals arriving at the onboard receivers. The enhanced performance of the proposed filtering technique is evidenced both through extensive numerical simulations and with experimental data obtained in field tests at sea. The tightly coupled filter is also shown to be able to operate closer to theoretical performance lower bounds, such as the posterior Cramér‐Rao lower bound, using Monte‐Carlo simulations. This paper details the design and description of an USBL/INS prototype to be used as a low‐cost navigation system, including the acoustic processing and positioning system, fully developed in‐house. The developed system validates the usage of the proposed technique with real data in real world operation scenarios, and its enhanced performance compared to classical strategies is evaluated experimentally (median improvement level of 15% in typical operating conditions). Improved and faster convergence to nominal trajectories from multiple initial conditions, as well as enhanced accelerometer and rate gyros estimation capabilities, are also demonstrated experimentally for the new tightly coupled filter.
Growth stage determination plays an important role in yield prediction and cereal husbandry decision-making. Conventionally, crop growth stage determination is performed manually by means of visual ...inspection. This paper investigates wheat and barley growth stage estimation by classification of proximal images using convolutional neural networks (ConvNets). A dataset consisting of 138,000 images captured prior to the crop canopy closure stage was acquired from 4 sites (7 different fields) in Ireland. The dataset includes images of 12 growth stages of wheat and 11 growth stages of barley captured for a number of crop varieties, seed rates and brightness levels. A camera was held at 2 m from the ground and two camera poses were used—downward-looking and declined to
45
∘
below the horizon. Classification was carried out using three different machine learning approaches: (1) a 5-layer ConvNet model, including three convolutional layers, which was trained from scratch on our crop dataset; (2) transfer learning based on a VGG19 network pre-trained on ImageNet with an additional four fully connected layers, and (3) a support vector machine with conventional feature extraction. The classification accuracies of the aforementioned models were found to be (1) 91.1–94.2% for the ConvNet model, (2) 99.7–100% for the transfer learning model and (3) 63.6–65.1% for the SVM. For both crops, the best accuracy was obtained using the
45
∘
camera pose and the transfer learning ConvNet model. For the growth stage classification task, the transfer learning ConvNet has the advantage of significantly reduced training time when compared with the built-from-scratch ConvNet model.
The western-European hedgehog (
), in expanding its range towards human habitats, faces exposure to contaminants and biological agents, potentially leading to diseases associated with hematological ...and biochemical changes. As bioindicators of environmental pollution and carriers of zoonotic agents, hedgehogs play a crucial role in One Health studies, emphasizing the need for a comprehensive understanding of their clinical-pathological aspects. Exploring the blood reference values in healthy animals of this species is crucial for understanding and improving their well-being, and identifying possible diseases/pathogens that may affect its conservation and/or impact human health. This review is focused on analyzing the data available in the literature for
blood reference intervals. A comprehensive literature review of the studies published in Europe is performed, highlighting their specificities, and emphasizing the need for continuous research in this field. Our final goal is to provide a crucial tool for assessing the health status of the species, and underscoring the significance of research in this specific domain.
This paper addresses the problem of steering a group of vehicles along given spatial paths while holding a desired time-varying geometrical formation pattern. The solution to this problem, henceforth ...referred to as the coordinated path-following (CPF) problem, unfolds in two basic steps. First, a path-following control law is designed to drive each vehicle to its assigned path, with a nominal speed profile that may be path dependent. In the second step, the speeds of the virtual targets (also called coordination states) are adjusted about their nominal values so as to synchronize their positions and achieve, indirectly, vehicle coordination. In the problem formulation, it is explicitly considered that each vehicle transmits its coordination state to a subset of the other vehicles only, as determined by the communications topology adopted. To better root the paper in a nontrivial design example, a CPF algorithm is derived for multiple underactuated autonomous underwater vehicles. Simulation results are presented and discussed.
PDF
