Food properties, whether they concern the physical, thermodynamic, chemical, nutritional or sensory characteristics of foods, play an important role in food processing. In our quest to gain a mechanistic understanding of changes occurring during food processing, the knowledge of food properties is essential. Quantitative information on the food properties is necessary in the design and operation of food processing equipment. Foods, because of their biological nature and variability, vary in the magnitude of their properties. The variation in properties offer a challenge both in their measurement and use in the food processing applications. Often a high level of precision in measurement of properties is not possible as the measurement method may itself cause changes to the product, resulting in a variation in the obtained values. Recognizing the difficulties in measurement of food properties, and the lack of completeness of such information, several research programs have been in existence during the last two decades. In Europe, a multinational effort has been underway since 1978. The first project supported by COST (European Cooperation in the Field of Scientific and Technical Research), was titled COST 90 "The Effect of Processing on the Physical Properties of Foodstuffs." This and another project COST 90bis have considerably added to our knowledge of measurement methods and data on a number of physical properties. Two publications that summarize the work conducted under 1 2 these projects are Physical Properties of Foods and Physical Properties of Foods .

This book endeavours to highlight the untapped potential of Smart Agriculture for the innovation and expansion of the agriculture sector. The sector shall make incremental progress as it learns from associations between data over time through Artificial Intelligence, deep learning and Internet of Things applications. The farming industry and Smart agriculture develop from the stringent limits imposed by a farm's location, which in turn has a series of related effects with respect to supply chain management, food availability, biodiversity, farmers' decision-making and insurance, and environmental concerns among others. All of the above-mentioned aspects will derive substantial benefits from the implementation of a data-driven approach under the condition that the systems, tools and techniques to be used have been designed to handle the volume and variety of the data to be gathered. Contributions to this book have been solicited with the goal of uncovering the possibilities of engaging agriculture with equipped and effective profound learning algorithms. Most agricultural research centres are already adopting Internet of Things for the monitoring of a wide range of farm services, and there are significant opportunities for agriculture administration through the effective implementation of Machine Learning, Deep Learning, Big Data and IoT structures.

This book endeavours to highlight the untapped potential of Smart Agriculture for the innovation and expansion of the agriculture sector. The sector shall make incremental progress as it learns from associations between data over time through Artificial Intelligence, deep learning and Internet of Things applications. The farming industry and Smart agriculture develop from the stringent limits imposed by a farm's location, which in turn has a series of related effects with respect to supply chain management, food availability, biodiversity, farmers' decision-making and insurance, and environmental concerns among others. All of the above-mentioned aspects will derive substantial benefits from the implementation of a data-driven approach under the condition that the systems, tools and techniques to be used have been designed to handle the volume and variety of the data to be gathered. Contributions to this book have been solicited with the goal of uncovering the possibilities of engaging agriculture with equipped and effective profound learning algorithms. Most agricultural research centres are already adopting Internet of Things for the monitoring of a wide range of farm services, and there are significant opportunities for agriculture administration through the effective implementation of Machine Learning, Deep Learning, Big Data and IoT structures.

Food properties, whether they concern the physical, thermodynamic, chemical, nutritional or sensory characteristics of foods, play an important role in food processing. In our quest to gain a mechanistic understanding of changes occurring during food processing, the knowledge of food properties is essential. Quantitative information on the food properties is necessary in the design and operation of food processing equipment. Foods, because of their biological nature and variability, vary in the magnitude of their properties. The variation in properties offer a challenge both in their measurement and use in the food processing applications. Often a high level of precision in measurement of properties is not possible as the measurement method may itself cause changes to the product, resulting in a variation in the obtained values. Recognizing the difficulties in measurement of food properties, and the lack of completeness of such information, several research programs have been in existence during the last two decades. In Europe, a multinational effort has been underway since 1978. The first project supported by COST (European Cooperation in the Field of Scientific and Technical Research), was titled COST 90 "The Effect of Processing on the Physical Properties of Foodstuffs." This and another project COST 90bis have considerably added to our knowledge of measurement methods and data on a number of physical properties. Two publications that summarize the work conducted under 1 2 these projects are Physical Properties of Foods and Physical Properties of Foods .

Adoption of Micro Irrigation System can be a panacea in irrigation related problems. In this technology, the cropped field is irrigated in the close vicinity of root zone of crop. It reduces the water loss occurring through evaporation, conveyance and distribution. Therefore high water use efficiency can be achieved. The equations which are used to describe hydraulic phenomena are basically non-linear in character and, thus, cannot be solve directly. The finite element method is a systemic numerical procedure for solving complex engineering problems. The finite element analysis is based on matrix algebra and use of computers, because it is only in matrix form that the complete solution process can be expressed in a compact and elegant manner. Any continuous quantity can be approximated by a discrete model composed of a set of piecewise continuous functions defined over a finite number of sub-domains.

An account of the events leading to the withdrawal of the president's pleasure in respect of the chief of the naval staff, the constitutional and legal norms which should have been duly followed.