eChapters

ABSTRACT
Increased environmental pollution and high demand over supply for conventional fossil fuel sources have led to the exploration of other renewable energy sources. Out of the potential alternatives, methane has come up with a promising unconventional fuel source. Several technologies have been developed to establish methanation, including biomethanation, chemical methanation and gas-to-liquid technology. Several factors like process parameters, catalysts and reactors have been studied for process optimisation and making methane production commercially viable. Although methane as a greenhouse gas is a contributor to global warming, its combustion produces relatively ‘environment friendly’ gas CO₂, and H₂O. The released CO₂ is fixed into biomass by plant through photosynthesis process. Only rarely does methane combustion produces CO when combusted in an oxygen-limited condition. Thus, methane production and combustion are carbon neutral process. This chapter focuses on the application of methane as a source of alternate energy. Various technologies used, recent advances and challenges faced in methanation process are discussed.

Abstract

The term nano technology, buzzword of present day science owes its origin from the Greek word ‘nano’ literally meaning dwarf. It is expressed in terms of dimension one nanometer equals to one billionth of a meter (1nm=10-9m), work on the principle of particle movement, smallest particle accelerate fast in the system. The nano technology deals with manufacturing, study and manipulation of matter at nano-scale (or atomic scale) in the size range of  1-100 nm, called as nanoparticles (Rajan, 2004). Nano technology is one of the most fascinating and rapidly possessing potential to revolutionize in science and technology of medicine and agriculture. In plant pathology, nano technology has potential scope to detection, diagnosis and management of plant diseases. Micromechanical cantilever arrays for selective immobilization and fast quantitative detection of vital fungal spores (Nugaeva et al., 2005). Micro-fabricated chambers designed to mimic some of the features of xylem vessels and discovered that Xylella fastidiosa migrates via type IV pilus-mediated twitching motility (Meg et al., 2005). Antifungal properties of chitosan, chitosan-saponin and Cu-chitosan nanoparticle reveal against phytopatogenic fungi namely Alternaria alternate, Macrophomina phaseolina and Rhizoctonia solani (Sharan et al. 2013). 

1. Introduction

Biopolymers nowadays are grabbing a nice place in packaging industries replacing synthetic polymers. The most important advantage of biopolymer over synthetic polymers is that they are biodegradable and can be developed from agricultural or food processing wastes. Among the wide variety of materials currently used in food packaging, polymers have taken a major share because of their versatility and advantageous performance (Valdés et al., 2014). However, most polymers used for food packaging are not biodegradable or compostable and therefore represent an increasingly serious end-of-life disposal problem worldwide. Although food package stability during the shelf-life of the product is an advantage, it turns into a disadvantage when the packages enter the post-use phase.

ANN is a Mathematical model or Computational model based on biological neural networks. It consists of an interconnected group of artificial neurons and processes information using a connectionist approach to computation. Neural Networks are non-linear statistical data modeling tools. That can be used to model complex relationships between inputs and outputs or to find patterns in data.

Bioinformatics is a discipline that deals with computation of biological information. Bioinformatics is a newly emerging interdisciplinary research area spanning a range of specialties that include biology, biophysics, computer science, mathematics & statistics. It makes use of scientific and technological advances in the area of computer science, information technology and communication technology to solve complex problems in life sciences particularly problem in Biotechnology.

Explosive growth in biological data from large sequencing projects that are producing nucleotide sequences continuously at a faster rate and the content of the nucleotide database is doubling in every 14 months. The latest release of Gene bank (v.102) exceeded one billion base pairs. To cope with this huge volume of data, a new scientific discipline has emerged comprising bioinformatics, biocomputing & computational biology.

Introduction

After the advent of Post Genomic era, Biological data is accumulating at an electrifying pace every day. Storage and analysis of these data serve as a major source for scientific research to understand the phenomena of origin, evolution and existence of various forms of life. The management of these data requires different statistical techniques used for retrieval, storage, analysis and extraction of precise information from small as well as large biological datasets. Application of statistical tools in Bioinformatics especially in fisheries data has been reported (Roy and Martha, 2008).

Abstract

The protein classification prediction is an important Problem in molecular biology, and one that has attracted a lot of attention, because there is a gap between sequence and structure of proteins from various resources. The proteins can be usually classified into one of the four structural classes; they are all-a, all-b, a/b and a+b. To address the problem of protein classification, many different algorithms and efforts have been made so far. In this paper, a new rule based data mining method for the prediction of protein structural classes is constructed using Rough Sets algorithm. Rough Sets Theory (RST) is a new mathematical approach to study the realistic information (Z. Pawlak, 1982). It focuses on knowledge reasoning by the whole set directly approximating to the incomplete and uncertain information. There are studies on the knowledge reduction and features selection of mass data. To apply rough sets algorithm, a decision table is constructed using Amino acid compositions and eight physicochemical properties data as conditional attributes. The generated decision rules after reducing the decision system can be used to classify new objects.The classification results of Rough Sets is verified by using self-consistency and jackknife tests on the datasets constructed by G.P. Zhou and comparison is made with some of the previous works.

A large number of insect pests are associated with stored grains which are directly related to geographical and climatic conditions. There are different estimates on post harvest losses in food. During storage both quantitative and qualitative losses occur due to insects, rodents, and microorganisms. Almost all the insect species may destroy 10.0 - 15.0 % of grain and contaminate with undesirable odour. These pests also helps in transportation of fungi. Some insect pests initiate damage at the ripening stage of crops and continue during storage. Major sources of infestations are old gunny bags, storage structure and old containers (Pruthi and Singh, 1950). The spread and distribution of stored product pests are facilitated by movement of grains from one area to another and by flight of insect pests as some of the adult insects are strong fliers. The cracks and crevices are probable sites for cross infestation. Nearly one thousand species of insects have been associated with stored products in different part of the world. Majority of insect pests belong to the orders Coleoptera and Lepidoptera (Khare, 1994).

INTRODUCTION

Apricot (Prunus armeniaca L.), belongs to the family Rosaceae and is one of the most important fruit crop of mid hills and dry temperate regions of India. It was introduced in India by the European settlers and Missionaries in the late 19th century. Cultivated apricot has its origin in North-Eastern China, whereas wild apricot, popularly known as zardalu, appears to be indigenous to India. It grows wild in hills of Shimla and Kinnaur districts of Himachal Pradesh. Fruit is delicious, rich in vitamin A and contains more carbohydrates, proteins, phosphorous and niacin than many other common fruits. Besides its use as dessert, it is also canned and dried. Fruit is processed into jam, nectar and squash. The kernels are either sweet or bitter, depending upon the variety. The sweet kernels are used as a cheap substitute for almonds in pastries and confectionery. The bitter kernels are used for oil extraction. In India, apricot is grown commercially in the hills of Himachal Pradesh, Jammu and Kashmir, Uttar Pradesh and to a limited extent in north eastern hills. Some drying type apricots are being grown in the dry temperate areas of Kinnaur and Lahaul Spiti in Himachal Pradesh and Ladakh in Jammu and Kashmir.

In recent years, a new branch of biological science, called as bio-informatics receives more attention among its users and calls for application of computational statistical algorithms to a greater extent and needs employment of more sophisticated mathematical/statistical tools. Though biological science and information technology forms a major part in bio-informatics research as applied to agriculture, statistical tools act as their backbone. Its utility is more felt starting from the stage of framing of hypothesis till analyzing/interpreting results of a scientific experiment.  It can also be viewed as a three way multi-disciplinary approach with biotechnology, information technology and statistical technology as its three faces, with the principles of statistics applied to biological science through an interface information technology.

5.1. INTRODUCTION
     
Rice is an important provider of nourishment for the world’s population. Indian scented rice, ‘Basmati’ has dominated the domestic and international market for aroma. Aromatic rice is an important commodity worldwide and command premium price over non-scented varieties. Most of the trade in aromatic rice is from India, Pakistan and Thailand. Bulk of aromatic rice from India and Pakistan consist of Basmati, while Thailand is the supplier of Jasmine rice. The Indian subcontinent has the Natural Gift of basmati rice that has been accepted as the best scented, long and slender grain in the world markets and gets high price. In addition to Basmati, many local landraces are grown traditionally, which excel in aroma, grain quality and cooking quality. Most of these genotypes are short bold to medium bold grain and hence not traded in the international market. However, in the domestic market its demand is greater than the Basmati rice. These are mainly used for special preparation, such as Khir in Bengal.

The goats play a vital role in the economy of the poor and marginal farmers of rural India. Notwithstanding the fact that the goat population has shown a steady growth over the year’s very little effort has been taken for genetic improvement at farm level. As per 20th Livestock Census, 27.74% of the livestock population is Goats. Out of 148.88 million Indigenous Goats (Including Non-descript), 27.4% are pure breed, 9.1% are graded breeds and the remaining 63.5% are non-descript breeds. So, to increase the productivity per goat, we need to improve the breed quality scientifically. Artificial insemination (AI) using frozen semen is practiced to produce superior progeny and to accelerate the up gradation of stock. The conception rate with AI is lower but it has great potential to multiply superior quality of goat with faster rate. This technique also spread elite genetic material throughout a population with increased rate of genetic improvement. This technique is also important for the breed conservation process and has paved the way for other reproductive biotechnologies. The sufficient elite germplasm of male buck is not available throughout the country to cover breeding programmed by natural mating. AI is the best solution to improve the quality and productivity per goat.

The selection of breeding bucks in relation to maximizing the reproductive efficiency depends upon males. AI permits intense selection of sires with exceptional merits and provides opportunity to exploit the value of superior sires. Young males can be trained for exhibiting sexual behaviors and semen collection through the uses of male, anoestrus doe or oestrus doe as dummy. Successful AI depends on precise management of semen collection, its frequency and use. The semen collection implies mounting a teaser doe or a dummy. Artificial vagina (AV) and electro-ejaculator (EE) are the two methods for semen collection in bucks. AV method is being used as universal method for routine semen collection whereas electro-ejaculation is generally used for collecting semen from untrained and valuable sires incapable of service. Moreover, this method of collection is painful for the animals. Semen evaluation should be rapid and effective so that collected semen samples can be processed for initial quality which ultimately affects the fertility. There are several tests for the assessment of semen quality but no single test is reliable to give definite prediction of the fertility.

• What is Intelligence?
• What is Artificial Intelligence?
• Branches of AI
• Natural–Language
• Natural Language Processing 
• Natural Language Recognition
• Simple Natural Language Grammar
• Intelligent Technologies in Agriculture
• Intelligent Animal Houses
• Agricultural Robots

• What is a Neural Network?
• How does an Artificial Neural Network (ANN) work?
• Characteristics of Neural Networks 
• Architectures of Artificial Neural Networks
• Learning Process
• Classification of Learning Algorithms
• Artificial Neural Networks in Agriculture -Intelligent Agent 
• Classes of Intelligent Agents
• Characteristic of Intelligent Agents

Introduction

Modern agriculture has been of great help in alleviating hunger from the world, because the world population more than doubled itself during the last half of the 20th century; it increased from 2.5 billion in AD 1950 to 7.1 billion in 2012 (USCB, 2013). It is predicted that the world population will again double itself by the end of the 21st century and will touch the 12 billion mark. Most of this increase in population has been, and will be, in the developing countries in Asia, Africa and South America. India occupies 2.4 percent of the total land area of the world, but supports 16.7 per cent of the world population. Like many other developing countries in the world, population in India is increased from 345 million in 1947 to 1210 million as per the 2011 census with a growth rate of 1.76 during last decade. Therefore, pressure on land has been mounting up at an alarming rate. Population growth coupled with live stock population expansion, urbanization and industrialization are major contributory factors to it. The unscientific and unplanned exploitation of this limited resource takes its toll in terms of degrading the land. A large proportion of the land area shows clear evidence of advanced and continuing degradation seriously affecting the country’s productive resource base (Abrol and Sehgal, 1994). Jammu & Kashmir and  Nagaland  have maximum share of their land (94%) under degradation. This is primarily due to large areas under mountains, cold deserts and other such degraded lands. In the agriculturally prominent states like Uttar Pradesh (63%), Madhya Pradesh (50%) and Karnataka (46%) (Shalander Kumar, 2011) the extent of land degradation is of great concern and posing a big threat to the natural resources, resulting in almost 5 billion tonnes soil and 6 million tones of nutrient loss every year (Singh, 2009).

Introduction

Road traffic in cold snowy regions during winter season faces problems, like icing of road, snow compaction and snow storms that obstruct visibility. In snowy region there is also danger of damage due to snow avalanches. Avalanches often severely damage road service facilities or road structures. Quick response and corrective actions are required to cope with the damages, if any avalanche occurs.

Influenza a Pandemics

15.1    Banana Chips/Crisps
    
15.2    Banana Puree/Pulp
    
15.3    Banana Flour
    
15.4    Banana Powder
    
15.5    Banana Flakes
    
15.6    Banana Figs or Dehydrated Banana
    
15.7    Banana Jam
    
15.8    Ready-To-Serve (Rts) Beverage
    
15.9    Banana Beer and Wine
    
15.10    Banana Vinegar
    
15.11    Banana Catsup
    
15.12    Banana Inflorescence Relish
    
15.13    Candied Banana
    
15.14    Other Banana Based Products

INTRODUCTION

Banana (Musa species) also known as ‘Apple of Paradise’ is an important and commercial fruit crop of tropical regions of the world. It is the only tropical fruit traded to the extent, that it is the 5th largest agricultural commodity after cereals, sugar, coffee and cocoa in world market.

The word ‘banana’ is now applied to all table varieties. Formerly, it was applied to ‘Nendran’ banana of Kerala which was however called ‘Plantain’ by Westerners. The English used the word ‘Plantain’ to represent cooking banana while in parts of South India, even sweet fruited clones were called ‘Plantains’. The variant with persistent bracts and male flowers with large fruits held in lax manner and eaten after cooking were grouped under plantains. All other types which had small fruits, held compact in a bunch with softening of the pulp when ripe, dropping of withered bracts and staminate flowers as the banana. In other words plantain are starchy, not sweet and cooked as vegetable. They usually resembles green bananas, are longer and have thick skin. Bananas are sweet, shorter and have thinner skin. They are eaten as a fruit and have yellow colour when ripe.