Assessing corn water stress using spectral reflectance

2014 Summer.Includes bibliographical references.Multiple remote sensing techniques have been developed to identify crop water stress, but some methods may be difficult for farmers to apply. Unlike most techniques, shortwave vegetation indices can be calculated using satellite, aerial, or ground imagery from the green (525-600 nm), red (625-700 nm), and near infrared (750-900 nm) spectral bands. If vegetation indices can be used to monitor crop water stress, growers could use this information as a quick low-cost guideline for irrigation management, thus helping save water by preventing over irrigating. This study occurred in the 2013 growing season near Greeley, CO, where pressurized drip irrigation was used to irrigate twelve corn (Zea mays L.) treatments of varying water deficit. Multispectral data was collected and four different vegetation indices were evaluated: Normalized Difference Vegetation Index (NDVI), Optimized Soil-Adjusted Vegetation Index (OSAVI), Green Normalized Difference Vegetation Index (GNDVI), and the Wide Dynamic Range Vegetation Index (WDRVI). The four vegetation indices were compared to corn water stress as indicated by the stress coefficient (Ks) and water deficit in the root zone, calculated by using a water balance that monitors crop evapotranspiration (ET), irrigation events, precipitation events, and deep percolation. ET for the water balance was calculated using two different methods for comparison purposes: (1) calculation of the stress coefficient (Ks) using FAO-56 standard procedures; (2) use of canopy temperature ratio (Tc ratio) of a stressed crop to a non-stressed crop to calculate Ks. It was found that obtaining Ks from Tc ratio is a viable option, and requires less data to obtain than Ks from FAO-56. In order to compare the indices to Ks, vegetation ratios were developed in the process of normalization. Vegetation ratios are defined as the non-stressed vegetation index divided by the stressed vegetation index. Results showed that vegetation ratios were sensitive to water stress as indicated by good R2 values (Nratio = 0.53, Gratio=0.46, Oratio=0.49) and low RMSE values (Nratio = 0.076, Gratio=0.062, Oratio=0.076) when compared to Ks. Therefore it can be concluded that corn spectral reflectance is sensitive to water stress. In order to use spectral reflectance to manage crop water stress an irrigation trigger point of 0.93 for the vegetation ratios was determined. These results were validated using data collected by a MSR5 multispectral sensor in an adjacent field (SWIIM Field). The results from the second field proved better than in the main field giving higher R2 values (Nratio = 0.66, Gratio = 0.63, Oratio = 0.66), and lower RMSE values (Nratio = 0.043, Gratio = 0.036, Oratio = 0.043) between Ks and the vegetation indices. SWIIM field further validated the results that spectral reflectance can be used to monitor corn water stress

Where Are All the Women? Gender Bias Persists in Social Studies Texts

Introduction: Creating an inclusive and a more equitable classroom is a goal that all educators should continually strive for. One area of concern is that many girls and young women do not see themselves in curriculum materials - especially in the social studies

Knowledge Extraction From PV Power Generation With Deep Learning Autoencoder and Clustering-Based Algorithms

The unpredictable nature of photovoltaic solar power generation, caused by changing weather conditions, creates challenges for grid operators as they work to balance supply and demand. As solar power continues to become a larger part of the energy mix, managing this intermittency will be increasingly important. This paper focuses on identifying daily photovoltaic power production patterns to gain new knowledge of the generation patterns throughout the year based on unsupervised learning algorithms. The proposed data-driven model aims to extract typical daily photovoltaic power generation patterns by transforming the high dimensional temporal features of the daily PV power output into a lower latent feature space, which is learned by a deep learning autoencoder. Subsequently, the Partitioning Around Medoids (PAM) clustering algorithm is employed to identify the six distinct dominant patterns. Finally, a new algorithm is proposed to reconstruct these patterns in their original subspace. The proposed model is applied to two distinct datasets for further analysis. The results indicate that four out of the identified patterns in both datasets exhibit high correlation (over 95%) and temporal trends. These patterns correspond to distinct weather conditions, such as entirely sunny, mostly sunny, cloudy, and negligible power generation days, which were observed approximately 61% of the analyzed period. These typical patterns can be expected to be observed in other locations as well. Identified PV power generation patterns can improve forecasting models, optimize energy management systems, and aid in implementing energy storage or demand response programs and scheduling efficiently

Assessment of an Automatic Liquid Chromatograph for Foetal and Abnormal Haemoglobins

Peer Reviewe

EVALUATION OF ELECTRODE SURFACE TREATMENTS IN SLUDGE ELECTRO-OSMOSIS DEWATERING”

The drying of sludge produced by Wastewater Treatment Plants (WWTPs) is a very hard process due to the presence of the colloid fraction. Electro-osmosis could be a suitable technique to reduce the water content of the final sludge. Electrical fields of 10 V/cm, 15 V/cm and 20 V/cm have been studied for electro-osmosis tests in a static or dynamic apparatus, obtaining a dry solids content up to 40-45%, with respect to 25-30% obtained by mechanical methods. In order to optimise the apparatus, the corrosion behaviour of the anodic material appears the main critical aspect, due to the high circulating current density. Moreover, wear may be detrimental for the surface of rotating electrodes. We then investigated the behaviour of materials used as electrodes mainly by evaluating the efficiency of the process and their surface aspect after treatment. The full understanding of the electrochemical reactions developed at the anode are a key factor for the material choice. We compared the efficiency and the corrosion resistance of anodes made of titanium MMO with respect to bare stainless steel (AISI 304) and stainless steel coated by PVD technique with TiN, AlTiN and DLC. Characterization of the anodes samples by roughness tests and by AFM show that corrosion resistance of the DSA was the most suitable for our application. However, efficiencies of the electro-osmosis process for all the materials used have been found comparable, in terms of developed current densities and total energy consumptions, for low-test duration

Dynamic Model for the EV's Charging Infrastructure Planning Through Finite Element Method

The rapid increase in the number of electric vehicles around the world, the high demands on the charging stations, and the challenges for locating the charging stations made researchers around the globe to think for a proper solution. In this paper, a new method to locate EV's charging infrastructures, based on the parallelism between mobility needs and heat equation implemented with Finite Element Method analysis (FEM), is proposed. The method is applied for two cities with similar metropolitan area: Boston (USA) and Milan (Italy), with further results. Although FEM is a mathematical tool for solving physical problems, the behavior of different parameters in this paper is modeled as physical objects. In addition, the parameters are modeled according to the heat equation. Heat density maps are elaborated for the considered case studies. The two cities with extremely different characteristics are chosen to demonstrate the general application of the proposed method. Heat density maps show the likely demand points to establish charging infrastructures for EV's. The annual electricity consumption maps of the two considered cities are reported. The analysis of heat density and electricity consumption maps, together with the considerations of mains supply capacity can give a perspective for the location of charging stations in the future urban environments. The developed method contributes to deploy charging stations in an urban environment

Impianti di ionizzazione Cu-Ag per la di disinfezione delle acque e rischi di corrosione per spostamento

The copper and silver ionization system is one of the water sanitation treatments. Effective ionization occurs if the content of copper ions in solution is 0.2-0.4 mg/L and that of silver ions is 0.02-0.04 mg/L. An excess of copper and silver ions can react with other metal surfaces, triggering a deposition reaction, allowing the formation of deposits of more noble metals, and then promoting a localized corrosion phenomenon due to galvanic coupling. In the present paper, two case histories will be presented: one related to a legionella sanitizing plant system of a hospital; the second related to a system of water purification of a vessel on a boat. In both cases, working conditions are illustrated, corrosion morphology is described, focusing on the presence of copper and silver deposits, and the cause of corrosion is presented, estimating a reliable corrosion rate

Strategic Approach for Electric Vehicle Charging Infrastructure for Efficient Mobility along Highways: A Real Case Study in Spain

The Electric Vehicle (EV) market has been growing exponentially in recent years, which is why the distribution network of public charging stations will be subject to expansion and upgrading. In order to improve the public charging infrastructure, this paper aims to develop a model capable of analyzing the current situation of a stretch of highway, identifying the congestion points, created by the formation of queues at the charging points. A specific section of a highway in Spain was selected as a case study to evaluate the performance of the model, allowing for rigorous testing and thorough analysis of its performance in a real-world scenario. The first step is to define and evaluate the effects of factors affecting EV consumption, such as the slope of the road, weather conditions, and driving style. Subsequently, a simulation model is developed using the agent-based simulation software AnyLogic, which simulates the journey of a fleet of electric vehicles, taking into account the battery charging and discharging process. Based on the obtained results, the charging infrastructure is improved to minimize the total travel time of an electric vehicle on a long-distance trip

A New Theoretical Approach of Studying Resonances in Single Finline Transitions

In this article an innovative method of studying and removing the resonances, inherently exhibit by some waveguide to microstrip transitions, is presented. By modeling an equivalent circuit, this new approach allows to obtain the constructive parameters of a finline to microstrip transition, only using the values of the resistance and capacitance components of the equivalent circuit. This procedure will allow small microwave design Companies to realize these transitions only implementing circuit analysis software, and not having to afford electromagnetic analysis software, which are very expensive and time-consuming. A full 3D electromagnetic analysis confirms that the simulation results are in excellent agreement with the results obtained by the new equations discussed in this work