eChapters

Now days, in every walk of our life, we deal with a lot of information. It can be for personal use or family matters or for official or business matters. We store, process and retrieve variety of information. Information is basically the collection of various facts, records, statistics, formula or methods, which we use for our official work, for our research or for other use. When all these (information, we keep/ accumulate, for possible future use) are put in an organized manner, we find it convenient to use and easy to remember/ apply. Today, as it is rightly said, information is power; information is our knowledge-strength. It is thus important to organize and manage this knowledge that mostly depends on (and derived from) an information pool.

“Knowledge Management is the process by which an organization identifies, creates, manages and delivers information to enhance workforce performance. The purpose of knowledge management is to provide information collected from employees, best practices, clients, competitors and other sources in a format that employees can use to the productivity and quality of their work”

Before attempting to address the question of knowledge management, it’s probably appropriate to develop some perspective regarding this stuff called knowledge. Consider this observation made by Neil Fleming [1996] as a basis for thought relating to the following points.

Abstract

Cloud computing is becoming a technology mature enough for its use in genome research experiments. The use of large datasets, its highly demanding algorithms and the need for sudden computational resources, make large-scale sequencing experiments an attractive test-case for cloud computing. So far I have seen cloud computing demonstrated using R. However, it remains to be seen a rigorous comparison of its performance using a BLAST search and its ability to cope with ever-increasing databases and open source frameworks such as bioperl or bioconductor.

Introduction

The role of knowledge management as the key source for competitive advantage in our organizations has become a hotly debated topic. Indeed, it is a core competency for creating competitive advantage. In this environment that knowledge management is vital, therefore, at first we should determine knowledge management situation, and then to achieve a desired point, formulate a knowledge management strategy.

Abstract

Currently, computers are changing from single, isolated devices into entry points to a worldwide network of information exchange and business transactions called the World Wide Web (WWW).Current web contains billions of documents and has many administrative problems and limitations; in addition to that the web content is still accessible only to humans. For this reason, support in data, information, and knowledge exchange has become a key issue in current computer technology. The success of the WWW has made it increasingly difficult to find, access, present, and maintain the information required by a wide variety of users. In response to this problem, many new research initiatives and commercial enterprises have been set up to enrich available information with machine processable semantics.

Abstract
    
The amount of data being collected across a wide variety of fields today far exceeds our ability to reduce and analyze without the use of automated analysis techniques. In addition, the whole data may not be of user interest and imperfect. Therefore, it is very challenging to organize this data in formal system, which provides outputs in more relevant, useful, and structured manner. There are many techniques available to retrieve knowledge from this voluminous data. This paper discusses different rough computing based information retrieval techniques to obtain meaningful knowledge from large amount of datasets. We also discuss a real life example to show the viability of proposed research.

1. Machine Learning

Learning denotes changes in a system that enable a system to do the same task more efficiently the next time (Simon, 1983)or Learning is constructing or modifying representations of what is being experienced (Ryszard Michalski et al., 1986). Machine learning is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as sensor data or databases. A learner can take advantage of examples (data) to capture characteristics of interest of their unknown underlying probability distribution. Data can be seen as examples that illustrate relations between observed variables. Discover new things or structure that is unknown to humanseg. data mining.A major focus of machine learning research is to automatically learn to recognize complex patterns and make intelligent decisions based on data.

Introduction

The capabilities and effort to collect the geographic data has increased dramatically in the last decade to cope up with the increasing demand for the support of decision making and planning process in the state, national and global level.  From the Government sector, there is a need for spatial data to make quick responses to natural disasters, industrial accidents and environmental crises as actions will be decided based on geography. There is constant pressure to make wise decisions in a more time and cost effective and efficient manner. Accurate and current geospatial data are critical to these decisions.

Abstract

The study of computational toxicity prediction is very crucial and necessary, as it is quite time consuming and expensive to measure the toxicity via experimental techniques (Quan Liao et al., 2006). The use of computational approaches particularly to reduce the time and cost for the evaluation of the kinetic and toxic behaviour of any drug has been increased tremendously in recent time period (Richard Judson et al., 2004). Machine learning is a powerful tool to discover new complex combinatorial relationships in various in vitro and in vivo data information (Richard Judson et al., 2004) and has been successfully used in many diverse fields with numerous applications such as pharmacodynamics properties prediction (Czerminski et al., 2001; Livingstone et al., 2003), protein function prediction (Cai et al., 2003), medical decision making (Veropoulos, 2001), spam categorization (Drucker et al., 1999), detection of oil spills (Kubat et al., 1998), and speech recognition (Nuttakorn et al., 2001).

1. Introduction

With the fairly recent advent of inexpensive, rapid sequencing technologies that continue to improve sequencing efficiency and accuracy, many species of animals, plants, and microbes have annotated genomic information publicly available. It is important to use this genomic information for the identification and isolation of novel and superior alleles of important genes from gene pools of the organisms

Abstract

Fusion is a well known entity in various fields (e.g. medical imaging, weapon detection, flood monitoring etc.) that surmises information originating from several modalities. This chapter is an attempt to assort the various image fusion techniques available for human face recognition and to put a review of the advancements being made by the different researchers. The various types of fusion those have been used or may be used for face recognition have also been discussed here.

Abstract

Last few decades have witnessed an immense technological advancement in the education sector in India. With an advancement of technology, new gadgets are flooding the Indian market continuously bringing an immense opportunity for the education sector to improve upon the course delivery system. Higher education sector in India is adopting such new technologies in course delivery at a slow pace; however, there remains still a far way to traverse for the Indian education sector in order to achieve a perceptible and effective technology-infusion in the academic delivery arena. This paper is devoted to present an expository review on the usefulness of new gadgets, like smart phones, e-book reader as well as tablet PC, in both class-room education-delivery segments as well as in distance education sector in India.

Databases

A database is a collection of information that is organized so that it can easily be accessed, managed, and updated. Databases can be classified according to types of content: bibliographic, full-text, numeric and images and by their application area, for example: accounting, music compositions, movies, banking, manufacturing, or insurance. The term database may be narrowed to specify particular aspects of organized collection of data and may refer to the logical database, to the physical database as data content in computer data storage or to many other database sub-definitions.

Introduction

Data Mining is a complex subject that describes a type of database application used to search large amounts of data for patterns using specific tools. Advanced statistical methods and tools such as classification, association rule mining and cluster analysis search large volumes of data for previously unknown relationships within the data. Data Mining can be used to decipher trends in a wide variety of fields such as computer science, the marketing and advertising of goods, services or products, artificial intelligence research, biological sciences and high-level government intelligence. Data mining is a logical process that is used to search through large amounts of information in order to find important data.

Key words : CAVD, Drug Design, Bioinformatics, CADD, Co-factor, Vaccinology, infectious diseases, Jenner, immunity, Molecular modeling, Immunoinformatics, Antigen, Antibody, Live Vaccine, Alive Vaccine, Protein-peptide, Enzyme, Tools for Vaccine design,
 
Vaccine – Prevention is Better than Cure

A vaccine is a biological preparation that improves immunity to a particular disease. A vaccine typically contains an agent that resembles a disease-causing microorganism, and is often made from weakened or killed forms of the microbe, its toxins or one of its surface proteins. The agent stimulates the body’s immune system to recognize the agent

1. Introduction

Protein–protein interactions serve as the hub of the functioning of a living cell, coordinate biological processes as well as form core for interactomics system of living organisms. Various biological processes as signal transduction, cell-cell communication, ingestion or expulsion of any macromolecule, host parasite interaction, diseases as cancer and many other metabolic networks employ protein–protein interactions. During such a process two or more proteins interact transiently with each other or form complex for a long period of time. Thus attempts have been made for years to study comprehensive mechanism of such protein–protein interactions by various branches of sciences such as biochemistry, quantum chemistry, molecular dynamics, chemical biology and signal transduction. The availability of three-dimensional (3D) structure of proteins is a prerequisite for understanding functions of protein complexes at a molecular level as well as amino acid interactions within a complex.

Abstract

Protein-protein interactions play a major role in most cellular processes. Many essential cellular processes such as signal transduction, transport, cellular motion and most regulatory mechanisms are mediated by protein-protein interactions. The study of protein-protein interactions is of great importance in determining the biological function and impact of proteins. The experimental techniques remain expensive, time-consuming and labor-intense. Computational methods play an important role at all the stages of determining protein-protein interactions. In this chapter, we describe the different types of protein-protein interactions, computational methods, currently available databases and tools, protein-protein docking and as well as protein-protein interactions as drug targets.

Abstract

The field of bioinformatics emerged as a tool to facilitate biological discoveries more than 10 years ago. Structure prediction is fundamentally different from the inverse problem of protein design. Protein structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry; it is highly important in medicine and biotechnology. Structure prediction is fundamentally different from the inverse problem of protein design. While the genome of many organism have been sequenced over the last few year, transforming such raw sequence data into knowledge remains a hard task. A great number of prediction program for genes have been developed hat try to address this problem, which consists of locating the genes along a genome.

The term bioinformatics was coined by Paulien Hogeweg in 1979 for the study of informatics processes in biotic systems. It was primarily used in genetic and genomic studies, particularly in those areas of genomics involving large-scale DNA sequencing. Bioinformatics involves application of information technology to store, organise and analyse the vast amount of biological data available in the form of sequences and structures of proteins (the building blocks of organisms) and nucleic acids (the information carrier). There are umpteen ways to define bioinformatics, mainly owing to its rapid evolutions.

Establishment of databases and data warehouse; knowledge discovery from database/data warehouse (KDD) and development of the mechanism of dissemination of knowledge on information networks as per requirements of user groups is gaining importance now a days. Since there is a large number of data collection agencies and equally diverse resources for which the information is collected, it is easy to visualize the heterogeneity of information. The problem is compounded by the fact that there are no common standards that are applied in data collection. Designing data warehouses to integrate the collected information poses a formidable challenge to any data warehouses architect. In order to use the information for planning and decision-making level, data have to be integrated and aggregated properly.

Abstract

Crop cultivation is a complex process and involves a set of activities like land preparation, planting, pest control, irrigation, nutrient management, harvesting, marketing, etc. Entire cycle of crop production requires multitude of information by the farmers. Despite many efforts over the years to disseminate and transfer agriculture knowledge to the stakeholders, large amounts of expertise and knowledge are still out of reach to most of them. Agriculture knowledge may be contained in the corporate database, or it may reside undocumented inside the brain of the researchers or even stored in locations unknown to the majority of the people in the organization. Large sections of the farming community, particularly the rural folk, do not have access to the huge knowledge base acquired by agricultural universities, extension-centers and businesses. In this respect the main challenge is to find this knowledge and apply it to the decision making process involved in agriculture development.

1. Introduction

An expert system is defined as “a computer program designed to model the problem solving ability of a human expert” (Durkin, 1994). It is also defined as “a system that uses human knowledge captured in a computer to solve problems that ordinarily require human expertise”. An intelligent computer program that uses knowledge and inference procedures to solve problems that was difficult enough to acquire significant human expertise for their solutions. It is a computer application that solves complicated problems that would require extensive human expertise. To do so, it simulates the human reasoning process by applying specific knowledge and interfaces. Expert system also uses human knowledge to solve problems that normally

Introduction

ICT may be defined as technologies that facilitate communication and the processing and transmission of information by electronic means. ICT is an acronym that stands for Information Communications Technology and refers to technologies that facilitate communication and the processing of information by electronic means and includes everything from radio and television to telephones (fixed and mobile), computers and the internet. Information and communication has become an increasingly powerful tool for improving the delivery of basic services and enhancing local development opportunities. Recent years have seen increases in the use of ICT in almost all spheres of rural life. Especially, the rural communities require information among others on supply of inputs, innovations, improved technologies, credit, market prices and competitors. Since the concepts, methods and applications involved in ICT are constantly evolving on an almost daily basis. It’s difficult to keep up with the changes - they happen so fast.

Evolution of Computer technology and advent of database concept have provided enormous opportunities to the  scientist, researchers and managers of diverse field  to create, manipulate integrate, link and analyse their data in order to generate information and knowledge. The research projects involving exploration, survey and collection of data, generally create database to maintain and analyze the data.  Almost in every sphere of life and industry this database concept/technology is used in one form or other.  Scientists and researchers of life sciences realized the importance of the database and used this technology to develop databases of different types/groups of living organisms. The database technology has eased the difficulty in designing, developing and maintaining the complex information systems.

Introduction

“Quality” of fish refers to the aesthetic appearance and freshness or degree of spoilage which the fish has undergone or involves safety aspects such as being free from harmful bacteria, parasites or chemicals. “Quality’’ is a term which must be defined in association with an individual product type. For example, it is often thought that the best quality fish is the one which is consumed within the first few hours of post mortem. However, very fresh fish which are in rigor mortis will be of hard texture and difficult to fillet and skin are often unsuitable for smoking or drying. Thus, for the processor, a slightly older fish which have passed through the rigor process are more desirable.

Introduction

Northeastern Region of India consists of eight States, viz., Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Tripura and Sikkim.  The northeastern states are located between geographical ordinates, 21° to 29°30' N and 89°46' to 97°30' E. The region, surrounded almost on all sides by Bhutan, China, Myanmar and Bangladesh, which can be broadly divided into two characteristic zones viz., Mountainous and Plain. Although distinguished in the altitude differences, both the mountain and plain are closely interrelated in terms of natural resource sharing and economic flow. According to the physiographic characters this region is divided into five physiographic units, the Assam Himalayas, the Brahmaputra valley, the Shillong plateau, the Barak valley and the Southeastern hill region. Except the Brahmaputra and Barak valleys in Assam and the Imphal valley in Manipur, the terrain is hilly and mountainous, only making 65% of the northeast an undulating land with elevations ranging from 200 to 900 m above MSL

1. Introduction

Antheraea assamensis is lepidopteron insects of Assam which is commercially utilized for the heritage golden silk “muga”. Rearing of muga silkworm is one of the most significant traditional handloom industries restricted only to the North Eastern Region of India (N.E. India) and plays a major role in the rural economy.  Considering the ecological conditions, food plant distribution, presence of eco-types and species of diverse nature in co-existence, it is speculated that this region is a possible home of origin of Antharaea, from where radiations would have occurred (Neog et. al., 2010). Despite the fact that N.E. India is the original home of muga, earlier studies have shown that the population is declining due to depletion in genetic variability (www.cdfd.org.in/wildsilkbase/info_moths.php).

What is Indigenous Knowledge?

Indigenous knowledge (IK) is the local knowledge which is considered as the social capital of the poor. It is their main asset to invest in the struggle for survival, to produce food, to provide for shelter and to achieve control of their own lives. Indigenous knowledge is a cumulative body of knowledge, practices and manifestations maintained and developed by people with long histories of interaction with their natural environment. It forms the basis for local-level decision-making in agriculture, health, natural resource management and other activities, especially for the poor, and provides problem-solving strategies for communities (World Bank, 1998). IK is a tacit knowledge that is not easily codifiable and unique to a particular culture and society.

Introduction

Indigenous peoples established distinct systems of knowledge, innovation and customary practices from their centuries old interactions with the local biodiversity and environment, relating to the uses and management of local natural resources. Today, this knowledge is looked as an important resource for research and development in different areas such as pharmaceuticals, agriculture, veterinary, jewelry, fashion and cosmetic products. This has led to rampant exploitation of such knowledge disregarding the customary practices and rules of indigenous peoples holding and preserving such knowledge as well as the biodiversity and natural resources. As a consequence, the traditional knowledge is under threat of being misappropriated or lost.

Introduction
 
Intellectual property is a cluster of legally recognized rights associated with innovation and creativity, the works of the mind, as against physical products, land and other tangible resources. Even though it is intangible, intellectual property (IP) is often recognized as personal property, to be sold and traded like other forms of property. Under intellectual property law, owners are granted certain exclusive rights to various markets, machines, musical, literary, and artistic works; discoveries and inventions; and applications. But national laws normally don’t define ‘intellectual property’ as a single property right. Instead, ‘intellectual property’ is used as a convenient general term describing a range of distinct legal rights, relating to literary, artistic and scientific works; performances of performing artists; phonograms, and broadcasts; inventions in all fields of human endeavour; scientific discoveries; industrial designs; trademarks, service marks, and commercial names and designations; protection against unfair competition and all other rights resulting from intellectual activity in the industrial, scientific, literary or artistic fields.

No society can ever desire to achieve a long-term goal of sustainable development unless it builds upon its own knowledge, traditions, ethical foundations and technological endowments. The knowledge of the people particularly in drought and flood prone regions, hill areas, tribal areas and other high risk environments, has to become a building block of new technological improvements. Knowledge happens when our expectations are belied, modified and sometimes confirmed. Because the asymmetry in our expectations is influenced by our access to resources, institutions, technology and cultural platforms, we get different kinds of knowledge, even when we confront similar situations Gupta (2005). In any community living close to nature, asymmetry in knowledge generation and its utilization is inevitable. The experts exist not just in our profession, but in every profession.

I am happy to note that the Indian Agricultural Research Institute, a premier national institute for agricultural research is celebrating the 100th year of its establishment. It is indeed quite fitting that JARI has chosen to celebrate this occasion by organizing a seminar on current scenario in temperate horticulture in Himachal Pradesh which is the second highest producer of temperate fruits in the country, I, therefore consider myself to be privileged to be a key speaker, and express my appreciation and gratitude to the organizers for giving me this honour and opportunity in this very important event.
 
The varied climatic and soil conditions in India provide enormous scope for cultivation of wide range of tropical, sub-tropical and temperate horticultural crops, The production of tropical and sub-tropical horticultural crops is confined to the plains, coastal and root hills of Indian mountain~ whereas, the temperate horticulture is monopoly of the hilly regions of the country. The production of temperate fruits in the country is spread over some fifteen states and union territories situated in the following regions.

Abstract

Himachal Pradesh has achieved a transformation in the horticulture sector during the last fifty years. The total area under fruits, which was only 793 hectares in 1950 has increased to 1.82 lakh Hectares during 2003-04, out of which temperate fruits alone cover an area of 1.20 lakh hectares. Fruit production has also increased from 1200 M.T. in 1950 to 6.92 lakh MT during 2004-05, with temperate fruits accounting for 5.92 lakh MT.  Around 4.64 lakh farmers are estimated to be involved in the fruit production programme and the fruit industry generates a gross domestic income of about Rs. 1000 crores annually. The existing problems and constraints have been identified and the remedial measures required to provide the desired impetus to the horticulture industry of the State, elaborated.

Abstract

The available data revealed that the area under temperate fruits in Uttaranchal was about 1.4 lakh ha, which was more than 60 per cent of total area under fruit crops, whereas the production per annum was to the tune of 44.50 per cent  of the total fruit production in the state. The productivity status of apple (1.38 t/ha) was very low as compared to national average productivity of 4.98 t/ha. Unfortunately, the prevailing constraints such as non-availability of elite planting material; lack of technical know how; dry land horticulture; high cost of production, lack of credit awareness and availability; small and fragmented land holding; old and senile orchard; lack of transport and communication facilities; poor mechanization; lack of efficient marketing system and post harvest infrastructure do not allow the farmers to take advantage of the emerging opportunities in temperate fruit production.

Abstract

Paradoxically, on one hand wild relatives of crop plants got utilized as donor parents in developing hybrids and on the other hand got lost due to lack of conservation of practices, thus genetic erosion. And temperate fruit genetic resources are no exception. Over dependence of growers/orchardists on modern high yielding cultivars and all round development led to neglect of valuable genetic resources of fruit crops. Yet, there are scores of examples where wild relatives have been exploited for genetic improvement of temperate fruits and nuts and still there exists a rich plethora of genetic diversity in the Himalayas which remains untapped and underutilized. Through the process of naturalization, several  elite genotypes, often referred to as geographical/ecological races and biotypes have emerged possessing unique characteristics valuable from horticultural point of view.

Abstract

India has now become the largest producer of fruits after China by producing 45.2 million tones of fruits from 3.78 million hectare area (NHB, 2004). India is first in the production of mango, banana, sapota and acid lime. India has also recorded highest productivity in grapes, sapota and acid lime in the world. India produces about 40 fruits commercially; however, the major share is from tropical and subtropical fruits like mango (28.17%), banana (29.43%), citrus (15.56 %), guava (3.97%) and grapes (2.76 %). Among temperate fruits apple has maximum area and production and 2. 98 % share in total production. Temperate fruits growing in India spread over some 18 states. These states are categorized into 3 major regions, namely, Northern Western Himalayan Region (NWHR), North Eastern Himalayan Region (NEHR) and other hilly areas.

Abstract

The potato research in India was started systematically after the establishment of Central Potato Research Institute (CPRI) in 1949. Forty-one potato varieties having attributes of early, medium and late maturity vis-à-vis resistance to various biotic and abiotic stresses have already been developed indigenously for varied agro-ecoregions in the hills and sub-tropical plains. After the establishment of CPRI, collection of potato germplasm was made mandatory. Presently there are over 2,700 accessions including 133 wild species (related to potato) in the germplasm collection of CPRI. Despite the large collection of potato germplasm at the institute the genetic base of all 41 Indian potato varieties released so far can be traced to only about 50 parents and most of these represent tetraploid potato cultivars while only a few of the exotic diploid wild species have been used in improvement of potato varieties in India. Under utilization of wild species could be mainly due to the pre- and post zygotic crossability barriers inherent in many species of genus solanum. Nevertheless, about seven wild species have been used in potato breeding for introgression of resistance genes for various biotic and abiotic stresses in the improved Indian potato varieties.

Abstract

The North-West Himalaya is bestowed with rich genetic diversity of minor temperate fruits representing the genera viz. Malus, Prunus, Pyrus, Rubus, Ribes, Sorbus, Cotoneaster, Myrica, Corylus, Crataegus, Punica, Hippophae, Elaeagnus, Viburnum, Vitis, Ficus, Citrus, Ziziphus, Morus,, Olea, etc. These species are known for their hardiness, adaptability to wastelands and tolerance to biotic and abiotic stresses. Apart from their easy availability, they assure some sustained yield and make our diet more diverse. Some indigenous species having potential for diversifying temperate fruit production are Pyrus pyrifolia, Diospyros lotus, Rubus ellipticus , R. lasiocarpus, R.. fruiticosus, Corylus colurna, Citrus pseudolimon, Hippophae rhamnoides and Pinus gerardiana. Some of the exotic temperate fruits viz. pineapple guava (Feijoa sellowiana), Chinese ber (Ziziphus jujuba), Japanese persimmon (Diospyros kaki), Rubus spp., Ribes spp, quince (Cydonia oblonga), medlar (Mespilus spp.), pecan nut (Carya illinoensis), hazelnut (Corylus avellana), husk tomato (Physalis spp.) and tree tomato (Cyphomendra betacea) have shown good performance at National Bureau of Plant Genetic Resources  Regional Station, Shimla.

Abstract

Genetic resource or germplasm are considered to the be the major building block of new varieties. However, on account of excessive pressures of development, deforestation and increasing  population, the valuable resources are fast eroding and a number of type have already been lost. If this trend is not checked the losses will continue. The germplasm has a pivotal role in the development of the fruit industry, hence, it is very important to, conserve, characterize and utilize the existing genetic resources as genetic resources are the common heritage of mankind and must therefore be made available to those who need them and must be suitably conserved to fulfill today’s and tomorrow’s demand through a systematic and well defined co-operative exchange network.

Abstract

The present studies were undertaken in selfed and open pollinated seedlings of 11 cultivars namely Belrubi, Blackmore, Catskill, Chandler, Fairfax,  Fern, Pajaro, Seascape, Selva, Tioga and Torrey during the years 2001 to 2003.  The days taken to 50%  flowering varied  from 43 to 64 days, flower number from 11.8 to 22.4 and pollen viability from 77.5 to 85.2%. The pollen germination was highest in 20% sucrose solution +  5 ppm boric acid in all the progenies.  The fruit length varied from 27.8 mm to 35.5 mm, breadth 21.3 to 27.9 mm, fruit weight 8.8 to 12.2 g, fruit firmness 0.23 to 0.33 lbs force, number of achenes per fruit 176.9 to 297.9, pedicel length 6.4 to 9.5 cm, TSS 8.1 to 12.3^ºB, titratable acidity 0.58 to 1.24%, total sugars 5.1 to 7.3, reducing  sugars 4.8 to 6.8% and non-reducing sugars from 0.50 to 1.11%.  Fruit development period  varied from 32.8 to 53.6 days, total number of fruits per plant 7.2 to 17.9, fruit yield per plant 27.4 to 57.3 g and fruit yield per plot from 0.77 to 1.40 Kg in different progenies.

Abstract

Indian Himalaya supports wide range of native and introduced temperate horticultural crops and important among them are Malus, Prunus, Pyrus, Juglans, Actinidia, Rubus, Hippophae in fruits; Allium, Amaranthus, Chenopodium, Fagopyrum, Phaseolus in vegetables, Aconitum, Gentiana, Picrorrhiza, Artemisia, Ephedra, Polygonatum, Podophyllum, Taxus, in medicinal and aromatic plants and number of orchids, rhododendrons, Rosa, Begonia, Primula, Delphinium and Tulipa in ornamental plants. Effective utilization of this vast range of horticultural genetic resources thus require their proper deployment which may include (i) use as a breeding material and/ or rootstocks, (ii) directly as variety through introduction or after selection, and (iii) as new crop though domestication. Except few successful examples in crops like Pisum, Phaseolus, Capsicum, Allium, and some ornamental crops, the picture of using genes from wild relatives is not very rosy.

Abstract

Apple productivity is declining gradually. It is the high time to find out new rootstock for apple improvement. The crab apples can play a pivotal role for the improvement of apple through proper utilization of their potentiality. A number of crab apples have been found growing wild in the Himalayas. Apple accessions collected from Shillong (Meghalaya) i.e. Malus baccata (Shillong), was found completely resistant to woolly aphid (Eriosoma lanigerum) and the development of root rot (c.o. Dematophora necatrix) and powdery mildew (Podosphora leuchotricha) was significantly delayed as compared to well known source of resistance, Malus zumi.  It has shown field resistance to apple scab (c.o. Venturia inaequalis) also.  It has a very good propagation potential.

Abstract

Investigations were carried out during 2005 at Rajgarh area of District Sirmaur in Himachal Pradesh for screening elite germplasm of Kaphal ( Myrica nagi Thunb). A wide range of variability was noticed for 14 fruit characters. Maximum fruit weight (834 mg), fruit length (12.94 mm), pulp weight (5.96 mg), pulp percentage (83.21%) and seed : pulp ratio (1 : 5.96) were recorded in Tree No. 35. maximum TSS (14.40 oB) was recorded in Tree No. 37. maximum fruit diameter (10.71 mm), fruit volume (650 µl), seed weight (154 mg) and seed breadth (7.51 mm) were recorded against Tree No. 25. maximum coefficient of variability was noticed for pulp weight followed by fruit weight and minimum for pulp percentage. Keeping in view the importance of large fruit size two elite trees (Tree No. 25 and 35) were marked which has fruit weight greater than 700 mg for collecting seeds to raise seedlings of this unexploited sub-temperate fruit

Abstract

The runners of ten strawberry cultivars were procured from different research stations, planted in the last week of October every year and mulched with paddy straw.  The earliest flowering was observed in Chandler, which produced the largest sized fruits (13.20 g) followedby Dana.(3.6 g). Higher incidence of fruit rot was observed in Chandler (26.2%) and least in the Sweet Charlie (9.3%). Sweet Charlie produced medium sized (11.80 g), highly glossy and attractive fruits having high TSS (10.2%), and minimum fruit rot can be better substitute for Chandler in sub-tropical areas.

Abstract

A promising strain/seedling have been identified that produces only male flowers (small and pink tinged) on the ventral side of the current season’s shoot all along its length. As many as 24 flowers per shoot were observed. The seedling continued to flower for about one month which attracts large number of honey bees. The pollen is also produced in abundance that dehisces early in the morning. Preliminary observations on the flowering behaviour and pollen studies have revealed that it can be used as a suitable polliniser for persimmon cultivars in general and Hachiya cultivar in particular.

Abstract

Considerable variation for different metric and non-metric characters was observed in seedling population of Pistachionut. The variation for non-metric characters was observed for precocity in flowering, colour of the kernel, shelling and splitting percentage. The studies have resulted in the identification of two pistillate and three staminate trees with desirable traits which can be exploited in breeding programme or used as elite planting material.

Abstract

In order to solve the problems of irregular bearing, lower yields and less colour development in apple, plants of different improved spur types and standard cultivars of delicious and other cultivars on EMLA 111 rootstock were imported from USA. Plants of different cultivars namely, Real Mecoy Red Delicious, Red Chief, Oregon Spur II, Criterion and Mutsu on EMLA 111 rootstock were planted at a distance of 15’x12’ with a density of 598 plants per hectare, in RBD design with 6 replications during 1989-90 at progeny cum demonstration orchard (PCDO) Anu (Jubbal). The observations were recorded during 1999-2002.

Abstract

In Himachal Pradesh, apple plantations have been made on seedling rootstock. The valley and comparatively warmer areas leads to the problems of irregular bearing and lower yields, besides less colour development in delicious varieties. Non uniformity in tree growth and yield is observed. To solve these problems, efforts have been made and plants of different cultivars of delicious and other prominent cultivars on different virus free clonal rootstocks have been introduced and planted at progeny-cum-demonstration orchard (PCDO) at anu situated at 1375m a.m.s.l. in Shimla district during 1989-90. Plant of three cultivars viz., Real Mecoy Red Delicious, Mutsu and Criterion on EMLA 26, EMLA 7a and EMLA 106 rootstock have been planted with a density of 1280 plants per hectare. The observations on yield were recorded during 1999-2002.

Abstract

Studies were carried out on 110 seedling trees of aonla growing at Tikker area of district Sirmaur, Ghanatti area of district Shimla and Kandaghat & Arki areas of district Solan to know the extent of divergence for various fruit characters by using non-hierarchical cluster analysis. Maximum co-efficient of variability was observed for fruit volume (38.63 %). First component gave maximum Eigen root value (7.286) and maximum percent variation (45.54 %). All 110 genotypes got clustered into eight clusters and the distribution of genotypes from different location was random. Maximum genotypes (30) entered in cluster 3 and minimum (5) in cluster 8. Intra-cluster distance varied between 1.877 (Cluster 5) to 3.137 (Cluster 8). The inter-cluster distance ranged between 3.006 (Cluster 3 & 4) to 11.677(Cluster 5 & 8). Wider genetic base is the prerequisite for breeding to get better recombinants and segregants. So, genotypes of Cluster 5 & 8 can be used for future aonla breeding programmes.

Abstract

In the hybridization programme, the horticulturally desirable female line HC-17- 11(susceptible) was crossed with powdery mildew resistant male line FC-1.  Over the years, the variety CHP-2 proved its stable resistance (average disease score 1.58 on 1-5 scale) to powdery mildew under natural epiphytotic conditions as well as supremacy in yield performance (11.7-28.0 t/ ha) over the check variety (10.3-16.5 t/ha) in different testing centers of AICRP(Vegetable Crops) and farmers’ fields (20-26 t/ha).Additionally, the pods are medium long (9.25 cm),light green,7-8 seeded with 48-52 per cent recovery of light green, sweet and tasteful  shelled peas. The shelled peas contain 1.4 per cent soluble protein and 9.5 mg ascorbic acid/100g of fresh shelled peas.