eChapters

Soybean (Glycine max L. Merr. 2n = 2x = 40, essentially a self-pollinated oil seed crop, family Leguminosae), also known as a miracle crop with on average 40% protein and 20% oil and one of the globally “Four Big Crops” namely rice, wheat, corn and soybean. As per FAOSTAT-2016, global soybean acreage, production and productivity are 121 million ha, 335 million tons and 2755 kg per ha for the year 2016. As per this statistics, top ten soybean producing countries are USA (108 million tons), Brazil (87 million tons), Argentina (53 million tons), China (12 million tons), India (10 million tons), Paraguay (10 million tons), Canada (6 million tons), Ukraine (4 million tons), Bolivia (3 million tons) and Uruguay (3 million tons).

Abstract

The groundwater behaviour in hard rock aquifer systems has always remained enigmatic owing to the heterogeneity of the aquifer systems. This is the reason why there are a lot of failures in groundwater targeting and management in hard rock aquifer systems even after the employment of many modern technologies. For precise groundwater targeting in hard rock aquifer systems various parameters like lithology, the type and the degree of structural deformation, the degree of weathering, geomorphology, etc., will have to be analysed which involves spatial analysis of voluminous data. In the sphere of spatial modelling, GIS plays an important role. Hence, a newer study has been carried out in parts of Madurai, Dindigul and Theni districts, Tamil Nadu, to identify the groundwater provinces and their functions using GIS. In the said study, GIS images were generated on the groundwater targets through GIS integration of transmissivity, permeability, storage co-efficient and water level. Such GIS image showing groundwater maxima was overlaid with GIS image of fracture maxima, subsurface geology maxima and the geomorphology maxima and thus by various GIS based spatial manipulations, aquifers controlled by structure, geomorphology, subsurface geology, and combinations of the above various variables were brought out. This has provided potential method for precise targeting of groundwater.

Energy, food production and various other natural resources are the limiting factors on this earth. The result of this bitter truth has been published in a book titled ‘The Limits to Growth’ in 1972. If the enormously growing population and the industrial process is not checked, then the earth’s civilization may come to an end within next hundred years.

By considering the space travel, we can very well understand about the Ecosystem. When we go away from the biosphere, it will be appropriate to develop unlimited environment through the energy accumulated from the sunlight in space. For the space travel for some days to moon and back to earth, we need not establish the entire ecological system as greater quantity of O₂ and food stuffs can be stored and CO₂ and other unwanted materials can be fixed for establishing space colonies, we have to build a special space ship with important abiotic components which can be recycled for use again and again. The vital processes of production, consumption and decomposition can be established and balanced through biotic components. In other words we are creating a complete mini human ecological machine. Before we established this system, we should be quite familiar about the space problems and its implications.

Abstract

Limits to crop production are shrinking land area under cropping, shortage and higher cost of irrigation water, fertilizers, pesticides, electricity, labour wages and harvest and post harvest losses due to non-availability of cold chains and storage spaces. Diversification of crops to high value products is yet to gain momentum. Restrictions in marketing due to APMC acts are to be reviewed and drafted farmer-producer friendly. Forcing of horticultural crops-vegetables, fruits, flowers, spices, aromatic crops-to market fresh produces during off season is getting attention and many such units are established as a part of urban and peri-urban horticulture. Ready to assemble forcing structures are now available. Hi-tech nurseries, integrated soil and water management through fertigation, pests and disease management by bio-pesticides, predators and parasitoids, pheromones and light traps are successfully demonstrated. Space saving horticulture focuses on maximization of productivity and minimization of inputs costs in an eco-friendly and sustainable way.

Key words : Remote Sensing, Ecosystem, Environmental Pollution, Biodiversity Conservation, Coastal Environmental Degradation, Wetland.

Introduction

National prosperity and human resources development are primarily shaped by the availability of natural resources and their use. None the less, the benefits are quite often negated by the resultant environmental degradation concomitant with their utilisation for economic values. The problems of environmental degradation have assumed critical dimensions in many parts of India due to resources exploitation; industrialisation and urbanisation, unchecked population growth and a never ending quest for energy to meet the increasing demands. Moreover, improper utilisation of resources has resulted in such environmental problems as soil erosion, waterlogging, floods, droughts and pollution of various types besides socio-economic disparity among people.

After the 1972 Stockholm conference on Human Environment and Development, there has been a phenomenal increase in the worldwide interest in the environmental issues associated with development. Consequently, the focus of development has shifted to environment friendly and sustainable developmental planning in recent years. The Rio Summit (June 3-14, 1992) further emphasised the fact that earth is an integral and interdependent system, which require sustainable developmental planning. During deliberations of the Rio Summit (Earth Summit), it was emphasised that satellite imagery will be quite helpful in monitoring earth’s environment.

India has a long tradition of environmental protection and has enacted laws during the last three decades to give further impetus to the conservation of natural resources and protection of environment. Some of the important laws are:

ABSTRACT

The estimation of the water requirement of crop is one of the basic needs for crop planning on the farm and for the planning of any irrigation project. Water requirements of crops include the losses due to Evapotranspiration (ET) plus the losses during the application of irrigation water (unavailable losses) and the quantity of water required for special operations such as transplanting and leaching of excess salts for crop growth. It is therefore necessary to estimate the ET and Crop Water Requirement (CWR) for the efficient use of water and increased crop production. In the present study, meteorological data were collected and the crop ET (ETc) and the CWR were estimated using FAO Penmann – Monteith method for the cropping pattern of the Buthangudy canal command area situated at a distance of 2Km from the popular village Sethiathope, Cuddalore district, of Tamil Nadu, India, which is located in between the Kumbhakonam – Chennai NH – 45 main road. The methodology combines the capability of GIS and CWR to produce maps showing spatial distribution of water resources over large areas.

Abstract

This paper presents a kinematic analysis for explaining the spatial and temporal variations of deformational structures in the Cuddapah Proterozoic orogenic belt, South India. This belt shows virtually undeformed, flat-lying sedimentary rocks in its western margin, whereas strongly deformed and folded rocks in the eastern boundary. The structural variations indicate increasing deformation in the east direction, implying a relative tectonic convergence from the east side. Based on the corner flow theory, we use a viscous model to determine the heterogeneous strain field in the asymmetric convergent zone, and explain varying deformations from the foreland to hinterland. According to this model, the strain field in the hinterland part varies in a pulsating manner with progressive crustal thickening, giving rise to multiple deformational structures in the course of a single continuous tectonic movement. We also studied the strain field in finite element models considering the gravity forces, and obtained similar results. The foreland vergence of deformational structures in the Cuddapah belt indicates a top-to-west horizontal shear during the overall horizontal contraction. Our numerical models show that this horizontal shear component in the foreland region is likely to be associated with a vertical shear component in the hinterland.

Introduction

All spatial data stored in a GIS are associated with a map projection, either implicitly (so-called “unprojected” data stored with raw longitude, latitude coordinates) or explicitly (where the data have been transformed into a known map projection). Map projections are a particularly important feature of spatial data because they introduce error and distortion, since a sphere cannot be transformed to a plane without some stretching and twisting of the sphere’s surface.

The typical GIS package supports anywhere from 5 to 50 map projection types, and most projections may be modified or customized by varying their parameters. This flexibility is important for two reasons First, in order to use two or more layers together in a GIS for visualization or analysis, all data must be projected in the same way. Second, certain types of analyses, such as the measurement of area, are only valid when using certain types of projections (and conversely, are completely wrong when using an inappropriate projection).

Introduction

Spatial data is different from a non-spatial data in the sense that it always has a spatial reference system which is nothing but a pair of coordinate values and a system of reference for these coordinates. For example, the locations of benchmark soil series of India can be defined as pairs of longitude and latitude in decimal degree values with respect to the prime meridian at Greenwich and zero latitude at the equator. The World Geodetic System (WGS84) is a frequently used system of reference on the Earth. The different types of spatial data are: (i) point, which is a single point location, such as a GPS reading or a geocoded address (ii) line, which is defined as a set of ordered points, connected by straight line segments (iii) polygon, an area, marked by one or more enclosing lines, possibly containing holes and (iv) grid, a collection of points or rectangular cells, organised in a regular lattice. Among the above said spatial data, the first three are vector data models and represent entities as exactly as possible, while the fourth data model is a raster data model, representing continuous surfaces by using a regular tessellation. In this chapter, we discuss how a spatial data can be handled in R. There are several packages available in R in which spatial data analysis can be handled e.g. sp, rgdal, raster etc. All the contributed packages for spatial data analysis in R address two broad areas: moving spatial data into and out of R, and analysing spatial data in R. In the following section, the sp package for spatial data handling is briefly discussed.

ABSTRACT

Soil is the medium in which the plant growth and development occurs. Soil type might change with genesis of the parent material and with prevailing weather conditions. Dominant soils of Tamil Nadu are Black soil, Red soil, Laterite soil and Hill soils. Each soil type has an inherent potential to retain and release nutrients to plants. The availability of nutrients varies from place to place and hence spatial distribution of nutrients, quantity of nutrients along with plant available water determines phenological development of crops. Nutrients are broadly classified as Macro and Micro nutrients that are required for crops in large and small quantities respectively. Availability of both macro and micro nutrients and its spatial distribution has not been attempted so far at a regional level. Such regional level approach of nutrients would suffice the researchers and policy planners to employ these data as inputs to Crop Simulation Models (CSM) in forecasting productivity of crops.

Thiruvannamalai district in Tamil Nadu is divided into 6 taluks, 18 blocks covering an area of 6,31,205 haof land. The district lies between 12⁰ 00’ to 12⁰ 55’ N latitude and 78⁰ 37'to 79⁰ 45’ E longitude. Red loamy soil is predominantly prevalent followed by black loamy soils. Generally paddy, groundnut, sugarcane, millets and pulses are cultivated during fasli season. This district was chosen as our study area.

A study has been attempted to map micro nutrients of Thiruvannamalai district. Geo-referenced surface soil samples from eighteen blocks of Thiruvananmalai district covering maximum soil units of soil map were collected randomly as per procedure adopted by soil survey manual. Global Positioning System (GPS) were used to collect corresponding geographic coordinates from each soil sampling point covering the entire Thiruvananmalai district by using Rikaline Bluetooth GPS 6031- X7 model. Approximately one thousand five hundred surface soil samples were collected, air dried, powered and sieved as per standard conditions. Soil samples were analyzed for its physical, chemical and fertility properties. Fertility maps for Micro nutrients such as Zinc, Iron, Manganese, Copper and Boron were plotted in ARCGIS Desktop. Micronutrients maps form a part of base map in analyzing and preparing an aggregated fertility map of Thiruvannamalai district.

Remote sensing images have an important characteristic known as spatial frequency. Spatial frequency is defined as the number of changes in pixel value per unit distance. Few changes in pixel or brightness value over an area in an image are known as low spatial frequency area like agricultural fields, forests, water bodies, etc. If the changes are large, then it is known as high frequency area like roads, built up areas, etc. Spatial filtering is an approach for extracting quantitative spatial information by taking into account the neighbouring pixel values along with the independent pixel value. Therefore, filtering is a technique for modifying or enhancing an image. Filtering is done to improve the interpretability of raster image or to extract certain information from them. It is a neighbourhood operation because the value of any pixel in the output image is determined by applying certain algorithm on the neighbourhood pixels of the corresponding input pixel. The nature of algorithm to be applied depends upon the information which user wants to derive from the raster image. Filtering operations are mainly done for smoothening, sharpening, noise removal and edge enhancement. A filter is a kernel of small array which is applied to input pixel and its neighbouring pixels in the raster. There are many types of filters which can be applied to a raster image in R. These types with their respective R – code examples are explained further.

Introduction

Activities to promote and monitor the growth of aquaculture inherently have a spatial component, because of the variations among biophysical and socio-economic characteristics from location to location. Biophysical characteristics may include water quality, soil type and climate. Socio-economic characteristics in aquaculture development may include administrative regulations, competing resource uses, market conditions, infrastructure support, and availability of technical expertise. Geographical Information Systems (GIS) provides the spatial information needed for decision-makers who evaluate such biophysical and socioeconomic characteristics as part of aquaculture planning efforts more effectively and timely (Kapetsky and Travaglia, 1995). GIS is potentially a powerful tool for assisting this class of decision-makers, and is already being effectively used for such purposes in some places (Carswell, 1998; Arnold et al., 2000) where advanced capabilities in terms of infrastructure and trained personnel exists. Nath et al. (2000) discussed various applications of GIS in aquaculture. In general spatial information technologies are being effectively used for sustainable management of aquaculture and inland fisheries. Some potential applications are as follows:

Abstract

A key problem in spatial-mathematical-model-based mineral potential mapping is the selection of appropriate functions that can effectively approximate the complex relationship between target mineral deposits and recognition criteria. This paper evaluates a series of spatial mathematical models based on different linear and non-linear functions by applying them to base-metal potential mapping of the Aravalli province, western India. Linear models applied are an extended weights-of-evidence model and a hybrid fuzzy weights-of-evidence model, while non-linear models are knowledge and data-driven fuzzy models, a neural network model, a hybrid neuro-fuzzy model and an augmented naive Bayesian classifier model. The parameters of the knowledge-driven fuzzy model are estimated from the expert knowledge, while those of the neural network and Bayesian classifier model are estimated from the data. The two hybrid models use both expert knowledge and data for parameter estimation.

As compared to the linear models, the non-linear models generally perform better in predicting the known base-metal deposits in the study area. Although the linear models do not fit the data as efficiently as the non-linear models, they are easier to implement using basic GIS functionalities and their parameters are more amenable to geoscientific interpretation. In addition, the linear models are less susceptible to the curse of dimensionality as compared to non-linear models, which makes them more suitable for applications to mineral potential mapping of the areas where there is a paucity of training mineral deposits. The hybrid models that conjunctively use both knowledge and data for parameter estimation generally perform better than purely knowledge-driven or purely data-driven models.

Mushrooms are regarded as a macro-fungus with a distinctive fruiting body which can be either epigeous or hypogeous and large enough to be seen with the naked eyes and to be picked by hand (Chang and Miles, 1992). Hundreds of identified species of mushrooms, since time immemorial, have made a significant global contribution to human food and medicine (Marshall and Nair, 2009). Mushrooms have been a part of the human diet and used as both food and medicine for centuries and their importance is well established in many spheres of human life as well as ecosystem functions. They are known to produce enough amount of protein rich quality food which is of high biological value and appropriate for all age groups. Edible mushrooms are recognized not only as delicacy but also as food in human diet. They are consumed not only for their innate ation and taste but also for their important nutritional value. 

3.1 Spawning Season

Striped murrel breeds in stagnant waters and commence breeding in ditches, ponds, tanks, flooded paddy fields, wetlands and dead end of rivers; a little prior to or with the onset of monsoons (Bhattacharya 1946; Chacko 1947). Striped murrel is a batch spawner species and hence breeds several times in a year. According to Courtenay et al. (2004), spawning occurs in this species all through the year. In northern states of India, the breeding season of this species coincides with south-west monsoon and extends from June to September with peak in mid of June to mid of August (Qasim and Qayyum, 1961). However, the species has been reported to breed during November to January in southern India (Alikunhi, 1953).

Blood transfusions, while life-saving, can sometimes result in adverse reactions. These reactions range from mild allergic responses to severe hemolysis or anaphylaxis. Prompt recognition and administration of appropriate antidotes are crucial to mitigate these effects and ensure patient safety. This chapter discusses the antidotes used in different species of animals for blood transfusion reactions, their doses, and species-specific considerations.
Types of transfusion reactions
I. Febrile non-hemolytic reaction: Caused by leukocyte antigens or cytokines in the donor blood.
II. Allergic reaction: Due to hypersensitivity to plasma proteins.
III. Hemolytic reaction: Immune-mediated destruction of transfused red blood cells (RBCs).
IV. Volume overload: Excessive fluid administration leading to pulmonary edema.
V. Anaphylaxis: Severe, life-threatening allergic response.

4.1 Introduction
There are special casting processes as listed below.
i. Shell casting
ii. Investment casting
iii. Ceramic mould casting
iv. Pressure diecasting
v. Centrifugal casting
vi. CO2 casting process
vii. Stir casting
viii. Squeeze casting
ix. Full mould casting
x. Magnetic casting
xi. Micro casting
4.2 Shell Casting
The complete aspect of shell casting has been already presented under shell pattern in Section 2.4.1.3. For the purpose of reinforcement, it is reproduced here. Sand that has been covered in resin is used as the mould in the casting process known as shell mould casting, or just shell moulding. After pouring molten metal into the mould’s cavity, the mould vaporizes to produce a hard shell. This process will have two or more patterns to give shape and size to the final product to be casted.
The steps of making shell mould are presented below.
1. In the case of two pieces of patterns, make each pattern using iron or steel.
2. A mould is made once the pattern has been made. In this stage, a lubricant is applied after both pattern components have been heated. After that, each pattern piece is placed at the top of a dump box which contains resin covered sand. Then the pattern will absorb the sand.
3. Invert the dump box to free the excess sand particles sticking the patten.

Cardiovascular examination provides essential information about cardiac function, circulation and vascular abnormalities. This chapter describes practical examination techniques including inspection, palpation, percussion and auscultation of the heart and peripheral circulation. Assessment of the cardiac impulse, heart sounds, murmurs, pulse quality, jugular veins and blood pressure contributes to identification of cardiovascular abnormalities. Electrocardiography is presented as an important diagnostic technique, including electrode placement and interpretation of standard leads. Echocardiography is also introduced for structural and functional cardiac assessment. The chapter provides species-specific practical approaches for cattle, horses and dogs, helping veterinary students recognize cardiovascular abnormalities systematically and accurately