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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.
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