eChapters

21.1 Introduction

Nanotechnology is an emerging field of science which is being highly exploited in the sphere of medicine where “nano” plays a vital role in delivery of drugs or chemical molecules to the point it is required in précised quantities in right proportions. Nanoscience infuses intelligence to the truck load of chemical constituents that are to be delivered at appropriate locations and cleave from the site after the task is complete. Such process will likely to reduce the cost besides ensuring environmental safety. Nanoscale devices with its unique properties make the agricultural system more smart and effective; such devices are capable of responding to different situations by themselves, thus taking appropriate remedial action with the need of external directions from humans. In short, these devices act as a detectors and if need arises serve as a solution/remedy for the particular issue. These smart delivery systems of chemicals in controlled and targeted manner can be considered synonymous to the proposed nano-drug delivery system in human (Patolsky et al., 2006). 

Introduction
1.1 Definition of Smart Energy Management (SEM)
Smart Energy Management is a smart practice that utilizes evolved and improved technologies for the analysis and enhancement of the energy systems in real-time. The main aim is to make energy production, distribution, and consumption more profi cient, affordable, and sustainable. SEM also focusses on minimizing the waste generated and environmental effects (Kataki et al., 2017). By the combination of advanced technologies such as Internet of Things (IoT), Artifi cial Intelligence (AI), Machine Learning (ML), optimization and transformation of bioenergy systems can be effectively achieved. This technology can also be used to monitor and control the bioenergy systems actively so as to complement the prerequisite of the implementation and operations in bioenergy plants successfully (Syed, 2024). The era of increased need for the renewable sources and alarming issues of climate alteration calls for the innovative energy management (Jones, 2017). It emphasizes the demand for SEM in bioenergy systems ensuring the production of sustainable, eco-compatible and structures bioenergy system. This chapter foreground the top causes for which SEM to be more vital for the future bioenergy prospects.SEM enables real-time monitoring and optimization which allows bioenergy plants and their production of energy according to the demand, weather conditions and availability of the feedstock (Swami et al., 2023). SEM also generates the way to regulate bioenergy systems to facilitate the cost, performance, and energy conversion efficacy by utilising sensors, statistics and cloud computing (Fig 1). The integration of SEM with bioenergy is specifically relevant because of the variable and complicated nature of biomass feedstocks which include forest and agricultural residues, and food waste (Rodrigues et al., 2022, Duca and Tascano, 2022). The variations such as, moisture, quality and energy density show the effect on the efficiency in the production of bioenergy. Smart technologies are used to monitor as well as optimize the energy production along with the real-time fluctuations in response to the demand, feedstock availability and its supply (Hao et al., 2022)
1.2 AI (Artificial Intelligence) ML (Machine Learning) and IoT
There are two major emerging technologies named AI and ML which have transformed SEM for bioenergy systems. These technologies ease predictive analytics, decision making and enhanced simple processes. By analysing the massive datasets gathered from bioenergy operations, AI systems are able to forecast future energy output, system efficacy and operational damage (Saju et al., 2025). Utilizing real-time data feed such as pH range, composition of feedstock, temperature etc, AI systems incorporated with bioenergy plants can forecast biogas generation in and anaerobic digestion system (Barasa, 2021). Algorithms of ML in SEM helps in analysing and enhancing decision making process by both live and historical data. It predicts the forecast pattern in energy output and modify the operational parameters. Consequently, through a continuous learning process over time, the forecast prediction and bioenergy system are becoming more and more efficient (Khan et al., 2022). Bioenergy systems such as feedstock transport, conversion processes, and energy distribution can have real-time data which are collected by IoT technologies, constituting sensors, actuators and other connected devices (Ahuja and Khosla, 2019; Wang et al., 2022). Intelligent energy management systems utilizing IoT and AI technologies can greatly improve the efficiency of energy distribution and use, contributing to more sustainable urban environments. According to Liew et al., 2021, sensors are the source of valuable insights for the operation of bioenergy because it helps the operators in make decisions about system performance and efficiency and gain a better knowledge of the system functions. Sensors are installed in bioenergy facilities to provide continuous monitoring of information such as temperature, moisture content, pressure, and gas composition using IoT. Figure 2 depicts the significance of AI, IoT and ML in renewable energy.

Smart farming, otherwise called smart agriculture, uses progressed agriculture advancements to improve ranch the farm management. By consolidating Industry 4.0 advancements, Precision farming achieves doable outcomes like extend production, resource insurance, and lessened petroleum derivative result. Internet of Things (IoT) accepts a fundamental part in Smart farming, by Precision agriculture to screen and deal with things, as a matter of fact. Information examination is in like manner essential for isolating huge encounters from the colossal proportion of data created by IoT devices. The reconciliation of present day modern digital technology has change into smart farming as information empowered and information driven activity. After affiliation, further examination of each IoT and data analytics frameworks in the agricultural region can be positive.
The total population is predicted to increase by 10 billion in 2050, by enhancing interest for agricultural goods, and notable food. This has brought about a developing interest supply befuddle. Issues including restricted assets, natural changes, and work deficiencies increment the jumble, endangering food security and agricultural production. To defeat these worries, farming should be feasible and utilize state of the art innovation. One important choice is “smart farming,” that attempt to increased food productivity by meeting the population demand in a sustainable manner. This is steady with the Assembled Countries’ Sustainable Development Goals (SDGs), which hold back nothing security utilizing reasonable ways.
Smart farming strategy for agriculture business had changed Ancient farming into smart agriculture. Ancient times, human cultivated the soil to provide food for livelihood. Such activity is known as agriculture, and it follow a long path between agriculture 1.0 to agriculture 4.0. Producers employed agricultural implements including pitchforks and sickles for cultivation throughout the 17th century, a period called as Agriculture 1.0. Farming practices, a huge number of workers are needed to conduct agricultural tasks. Moreover, agricultural

Cloud-based software is used for the management of financial and field activities of farms. Prior to computers, farmers maintained data manually by keeping lengthy records on papers. This method was prone to human calculation errors. After the computer boom in the 1980s, it was not long before finance software such as Money Counts came to market. 

Introduction 
The importance of climate change, sustainable development, environmental concerns, and energy needs are gaining attention more than ever. The conventional energy procedures, such as solely dependent on fossil fuels are ended with greenhouse emissions, contributing to pollution and deficiency in natural resources. To overcome these straits, bioenergy has become the sustainable and promising alternative, also offering the declining nature of dependency on non-renewable resources and parallelly providing cleaner energy options (Khalid, 2024). Mere the production of bioenergy is insufficient to address the huge energy needs of the current situation. If sustainability is to be ensured means, then effective energy management is to be ensured. The newly developed smart energy management systems improve energy production, distribution, and consumption by utilizing cutting-edge technology like artificial intelligence (AI), data analytics, and Internet of Things (IoT) devices. Smart energy management is a notion that limelight on lifting the reliability and efficiency of energy systems. With the usage of current technologies, smart energy systems can audit real-time energy use, and energy demands and manipulate the power distribution accordingly. This required to improvising the potential of renewable energy (Hossain et al., 2024). Energy recovery is defined as the reusing of energy, that has the possibility to get waste in the following forms, heat, waste materials, gas and so on. In the bioenergy industry organic waste is converted into a suitable form of energy, which gives hybrid benefits like waste reduction and energy generation. Furthermore, a highly resilient and efficient energy system that meets sustainable development goals can be created by combining these recovery systems with intelligent energy management tools (Mariana et al., 2021). The investigation of how energy recovery technologies and intelligent energy management can improve the efficiency and sustainability of bioenergy systems is covered in this chapter. The potential of smart energy solutions to meet the increasing need for sustainable and renewable energy sources will be highlighted in this research through a thorough analysis of case studies, emerging trends, and existing technologies. A roadmap for the future of bioenergy will be provided, together with an identification of the main obstacles and possibilities that players in this quickly changing industry must contend with (Naeem, et al., 2024).

11.1 Introduction

The application of greenhouse in agriculture is vast. Greenhouses are used for growing flowers, vegetables, fruits, transplants and varieties of certain crops in a controlled environment which is appropriate for the plants. The edible flowers are served in some good restaurants to grow them precise calculation is required. Sensor network can help to monitor and automate the activities in greenhouse. The objective of this chapter is to discuss the development of sensor nodes to monitor the growth of flower plants through XBee and internet of things. The system comprises of three sections- sensor nodes, local server and main server. Sensor nodes communicate to local server with XBee and then local server communicates the same data to main server through IoT.Fig.11.1 shows the generalized block diagram, sensor node is to be implemented on each flower pot and communicating to local and main server.

Introduction

Industry 4.0 is essentially the digital revolution of artificial intelligence and subsequent production processes utilizing contemporary smart technology. Cyber-physical systems, or intelligent machines, are the cornerstone of this revolution (Scoop, 2018). The key features of Industry 4.0 include the integration of IoT, increasing automation technology, and enhanced communication and self-counseling techniques (Tay et al., 2018). According to Schwab (2017), new developments in artificial intelligence (AI), robotics, nanotechnology, biotechnology, the Internet of Things (IoT), decentralized systems, 3D printing, fifth-generation communication technologies, quantum computing, and autonomous cars will all be part of this revolution. Early in the 2010s, Germany saw the emergence of Industry 4.0 as a result of government initiatives to advance manufacturing computerization as part of its high-tech strategy project. The concept of Industry 4.0 has been implemented in a variety of contexts and rebranded by various industries or businesses as needed.

Water system is considered an Arti?cial usage of the water on the dirt utilizing various strategies like siphons, cylinders and showers. Typically, the requirement for water system shows up where the precipitation is unpredictable, in dry times, or where lack of hydration is customary. An excessive number of water system frameworks are accessible with various sorts as indicated by the Climate of the dirt. The water utilized in water system has numerous assets, like underground water, through wells or springs; the surface water, from lakes, streams; or other a few sources, for instance, the treated wastewater or desalinated seawater. In this way, farmers need to save and safeguard their Agriculture water sources by limiting the capability of diseases. Since with any groundwater extraction, clients of water system water should be mindful so as not to deplete groundwater out with a rate more prominent than it is being recovered. There are two strategies of current water system systems, the conventional water system procedures and the Smart water system philosophies. Water system is like surface water system, trickle water system and sprinkler water system. Later on, a few extreme and confounded issues will be met by inundated agriculture. An illustration of a signi?cant issue is the low efficiency of the water assets for water system. An important safe guess is that over 40% of the diverted water system water is spent before at the level of the ranch, either through profound permeation or at the surface spillover. Nonetheless, frequently these misfortunes address botched open doors for water, as they keep water from showing up at the downstream redirections. One of the most noticeable coming issues is the expansion of various water prerequisites assets, for example, manufactural and metropolitan requirements. These are utilized to give water assets a higher worth, so as a result, researchers favor concentrating entirely on rehearses with a high inefficient rate. s worldwide populace is expanding quickly, rural efficiency in drylands needs improvement to fulfill food security needs. Subsequently, taking on Precision water system approaches is a suitable choice to more readily use the accessible water assets and further develop water efficiency in drylands. Water shortage has become one of the basic issues and undermines the supportable improvement

Efficient irrigation is essential for maintaining crop productivity while conserving increasingly limited water resources. This chapter explores the application of artificial intelligence to smart irrigation systems and irrigation scheduling. It considers water balance and evapotranspiration modelling and examines AI architectures used for irrigation decision-making. Sensor technologies and Internet of Things integration provide continuous information about soil, weather and crop conditions. Optimization algorithms can use these data to determine appropriate irrigation schedules and improve water-use efficiency. The chapter also discusses emerging AI-based irrigation approaches and global case studies. Challenges associated with implementation, data requirements, system limitations and ethical considerations are examined, followed by future directions for intelligent and sustainable irrigation management.

Water scarcity and inefficient irrigation are major constraints to sustainable agricultural production. This chapter presents smart irrigation as an AI-enabled approach for optimizing water application according to crop and environmental requirements. Smart irrigation systems integrate real-time information from soil-moisture sensors, weather forecasts, remote sensing, and crop growth models. Machine learning and predictive analytics can determine appropriate irrigation timing and quantities while reducing unnecessary water use. The chapter discusses the principles, components, technologies, and applications of AI-driven irrigation systems. It also highlights their contribution to improved crop productivity, nutrient-use efficiency, soil health, and climate resilience, while considering challenges such as investment costs, data accessibility, connectivity, and technological literacy.

Introduction

Bihar lies in the river plains of the basin of the river Ganga. It is endowed with fertile alluvial soil ground water resources. This makes the agriculture of Bihar rich and diverse. Bihar is one of the major producers of fruits in India with 6.7 percent of national production respectively. It ranks sixth among other States in the production of fruits respectively. Considering versatile climatic feature of Bihar, there is huge potential to grow almost all the fruits. The major fruit crops grown in Bihar are Litchi, Mango, Guava, Banana, etc. Minor crops like Makhana, Pineapple, strawberry are also grown.

Introduction

Recent advances in food technology have made our lives virtually easier and efficient. Changing lifestyle has led to the emergence of packaged food that provides convenience to the consumers. The authentic packaging of food implements consumers with the role of communication, containment, convenience, and protection. Any typical food package provides us with the information about the product and its nutritional fact, thus an efficient way of marketing/ branding. It protects the food product from the external environment and adulteration, thus keeps it safe. It allows the consumers to relish the food as per their convenience (reheating and direct consumption) and holds the product of any size, shape and restrains during handling and transportation (Robertson, 2006).

Food packages can be altered or modified according to one’s requirement with features like single-serving dishes and portability. However, traditional packaging is lacking adequacy to meet unending consumer demands and product intricacies. Therefore, a contemporary concept of packaging with higher proficiency is needed to meet various consumer requirements. For instance, a packaging that can - enhance product’s shelf-life with lesser or no preservatives, that maintains freshness, that meets permissible regulatory requisites and enables tracking throughout the product life-cycle. Emerging technologies like smart packaging have the expertise to invigilate a product and its milieu and pursue any modifications into these. Moreover, smart packaging helps in gaining global market recognition, and meets international food safety standards. In recent years, there has been rapid development in food packaging that includes active packaging, intelligent packaging, or smart packaging. These are the technologies that deal with the packaging of food, beverages, cosmetics, and pharmaceutical products. Moreover, these terminologies are apparently identical but, each has a different function to deal with and is as follows:

Conventional fertilizers often exhibit low nutrient-use efficiency, resulting in nutrient losses, soil degradation, water contamination and unnecessary production costs. Nano-fertilizers offer controlled and targeted nutrient delivery through formulations engineered at the nanoscale. Their high surface-area-to-volume ratio can improve nutrient availability, plant uptake, growth, bulb quality and storage performance while reducing conventional fertilizer requirements. This chapter explains the nature, modes of action and potential benefits of nano-fertilizers in onion production. It also considers nano-biofertilizers, smart nutrient-delivery systems and nano-sensors. Particular attention is given to manufacturing cost, nanotoxicity, effects on soil microorganisms, farmer accessibility and the need for standardized safety and regulatory frameworks.

Efficient nutrient and water management is essential for achieving high onion productivity without degrading soil and water resources. Excessive fertilizer use, poor irrigation practices, groundwater depletion, nutrient imbalance and climate variability can reduce input efficiency and environmental sustainability. This chapter presents soil testing, integrated nutrient management, site-specific nutrient application, microbial interventions, residue management, nanotechnology and digital soil mapping. It also covers drip and sprinkler irrigation, scheduling, fertigation, mulching, rainwater harvesting and other water-conservation practices. Technologies such as SPAD meters, GreenSeeker, GPS, GIS, drones, remote sensing, sensors, artificial intelligence and IoT systems facilitate real-time monitoring, need-based application and climate-smart management of agricultural resources.

Inclusive education requires learning environments that recognize and respond to the diverse sensory, physical, cognitive, emotional, and learning needs of students with disabilities. The integration of Generative AI with Assistive Educational Technology and digital pedagogy creates new possibilities for removing longstanding barriers to participation and achievement. This chapter explores how intelligent technologies can provide flexible, adaptive, and personalized learning experiences for disabled students. It examines applications involving text-to-speech, speech-to-text conversion, screen readers, captions, intelligent interfaces, eye tracking, gesture-based controls, AR/VR, multimodal content, real-time feedback, and AI-supported personalization. Generative AI can further enhance conventional assistive technologies by producing customized written, visual, and audio learning materials according to individual requirements. Universal Design for Learning provides an important framework for ensuring that these technologies support accessibility and inclusion rather than creating additional barriers. The chapter also highlights the importance of individualized learning plans, teacher preparation, family and community engagement, emotional support, and stakeholder collaboration. By combining digital pedagogy, assistive technologies, and GenAI, educational institutions can move toward more equitable, accessible, learner-centered environments in which students with disabilities can participate meaningfully and develop their full potential.

Plant breeding is a revered custom that proceeds with the most common way of creating further developed plant cultivars, which traces all the way back to the beginning of agriculture . People started to observe levels of greatness among the plants in their fields not long after the underlying regulations of cereal grains, from which they put away the seeds of the best to develop new harvests. Early plant-reproducing advancements were the trailblazers to such simple choice methodologies. Individuals from the whole way across the world investigated and developed almost 7000 assortments of food plants during Breeding 1.0, which started quite a while back. Breeding stage 2.0 began in the late nineteenth and mid 20th hundreds of years when an inbreeding discouragement was found. During this time, many advances in plant breeding were made in the study of reproducing itself, like duplicated field preliminaries, controlled intersections, factual examinations, formal exploratory plans, crossover breeding, family-based appraisals of reproducing values, and exact yield estimation at scale (e.g., with Muldrow joins). Breeding 3.0 came to around a long time back, when sub-atomic markers and genomic information started to enhance phenotypic information. Breeding 4.0 is quickly drawing nearer, with immense omics information and the fast advancement of informatics innovations. Starting from the start of the plant breeding cycle, beginning from crop training, new methodologies interceded by various mechanical upheavals are being advanced in the science consistently to build the speed, exactness, and Precision in plant reproducing. In the previous 10 years, this science has proactively brought the green upheaval by creating semi-predominate, supplement responsive, and crossover cultivars. In any case, taking into account the populace development, diminishing arable land, and Climate changes, these have requested more exact, high throughput moves toward that can intervene to foster harvest cultivars at a more prominent speed, with higher exactness, and accuracy. In such manner, the field of Artificial brainpower has as of late arisen, which has been recommended to have unprecedented potential to help with breeding Climate versatile Precisionyields. Climate strong harvests keep up with or increment crop yields

The fate of smoke from a wild land fire depends in large part on the airflow carrying it away from the fire which can involve a complex interaction of eddies that may occur near the ground or expand beyond the atmospheric mixed layer (Fig.11.1). The buoyancy of smoke and ambient atmospheric conditions determines how high and how quickly the smoke rises, and thus where it travels.
The smoke plume distribution is affected by number of factors as indicated below:
• Elevation: The smoke plumes at higher elevations disperse the smoke particles more vertically while plumes from lover elevations disperse more horizontally.
• Temperature: The large difference between the smoke and surrounding air affects the Plume dynamics. The buoyancy force increases the vertical velocity of the particles, while heat diffusion increases surrounding air temperature.
• Moisture: The presence of moisture can modify the distribution of smoke and chemistry of smoke particles.
• Topography: Topography can influence emissions that remain within the mixing zone.
• Atmospheric stability: Atmospheric stability can affect the distribution of smoke.

Smoking is an ancient method of food preservation, which is also known as smoke curing, produces products with very high salt content (>10%) and low water activity (~0.85). Smoking is a process of treating fish by exposing it to smoke from smouldering wood or plant materials to introduce flavour, taste, and preservative ingredients into the fish. This process is usually characterised by an integrated combination of salting, drying, heating and smoking steps in a smoking chamber. The drying effects during smoking, together with the antioxidant and bacteriostatic effects of the smoke, allow smoked products to have extended shelf-life. Smoked seafood includes different varieties like, smoked finfish and smoked bivalves. Many of the smoked products are in the form of ready-to-eat.

Developments of modern food preservation technology, such as pasteurization, cooling/refrigeration, deep-freezing, and vacuum packaging, have eclipsed the preserving functions of many traditional methods including smoking. Nowadays, the main purpose of smoking has been shifted for sensory quality rather than for its preservative effect.

Depending upon how the smoke is delivered into the food and smoking temperature, four basic types of smoking can be defined: hot smoking, cold smoking, liquid smoking, and electrostatic smoking. Hot smoking is the traditional smoking method using both heat and smoke, which usually occurs at temperatures above 70 °C. For smoked fish and fishery products, a minimum thermal process of 30 min at or above 145 °F (62.8 °C) is required by FDA (2001). Therefore, after hot smoking, products are fully cooked and ready for consumption.

ABSTRACT

Hyperspectral data are generally noisier compared to broadband multispectral data. Therefore, it is desirable to smoothen the reflectance spectra. Smoothing needs to preserve an absorption feature while simultaneously removing noise. It is very essential to optimize the smoothing filter to minimize disturbances to the statistical properties of the original data. This study was carried out to see the effect of Fast-Fourier Transform (FFT) based smoothing technique on the statistical properties of vegetation spectral response and to see the effect of the filter size. The data used for the present study is the reflectance spectra data obtained from space borne EO-1 onboard Hyperion sensor. Filter sizes were varied between 3 and 15 with the increment of 2, i.e. 3, 5, 7..........15. Paired t-test was carried out between the original and the smoothed data (for the selective bands) for all the filter sizes in order to see the extent of distortion with changing filter sizes. Our study revealed that the distortion in the spectra increases with the increase in the filter size. Beyond filter size 11, the number of locations within the spectra where the smooth spectra were statistically different from its original counterpart increased to 14 and reaches 21 at the filter size 15.

Botany:Snake gourd belonging to the family Cucurbitaceae native to Southeastern Asia and Australia but cultivated throughout the world for its curved and oddly shaped fruits that appear like snakes hanging on the supports or ground. This subtropical plant grows very fast in warm climates and produces lots of fruits for a long time. It is suitable for growing for home garden and fresh market.

Climate and soil: Snake gourd is adapted to wide variety of soil and climatic conditions. It requires a minimum temperature of 18^oC during early growth, but optimal temperatures are in the range of 24–27^oC. Snake gourd tolerates a wide range of soil but prefers a well drained sandy loam soil that is rich in organic matter. The optimum soil pH is 6.0–6.7, but plants tolerate alkaline soils up to pH

Varieties: CO1,CO2, PKM 1, PLR 1 and PLR 2.

On the morning of 13 Oct 2023 morning (9:30 am - 12:00 pm), ITAF participants visited snake-skin gourami local farms in Samut scorn province. Snake-skin gourami is one of the best delicacies in Thailand which has large demand in local and international markets. Snake-skin gourami can breed after reaching 100-200 gms ( 2 months). The culture period of snake- skin gourami is 9-10 months. In snake- skin gourami males have a large body and long dorsal fin than females.

Farm 1

Snake-skin gourami culture is done in 30 rai ( 1 rai= 1600 m2) area of the farm. The depth of the pond is 1.5m. A single crop is taken in one year. 50,000 no. of fry are stocked in 30 rai area. Feeding areas are constructed by the net embankment where feed is given to fish harvesting is done after 8-9 months. The cost of production for one crop is 2 million/year in that they produce 30-40 tonnes /30 rai, which is almost 3 million / year.

I. FILL UPS

1. The viability of pollen grains in snakegourd is for _____.
2. Stigma receptivity is for _____hours after opening.
3. The isolation distance for snakegourd foundation seed production is _____.
4. The wild species of snakegourd is _____.

INTRODUCTION

In many cultures, fresh cut flowers are deeply symbolic, conveying the message of nature to man. In recent times revolutionary changes have been seen in Indian floriculture sector which is due to the introduction of various annuals from abroad. Snapdragon too is the one of the relatively recent introduction in the field of cut flowers. Now-a-days, snapdragons are usually grown as annuals, though traditionally they are cultivated as perennials. Due to its curious shape of flowers, which resemble a dog, rabbit or dragon, it is popularly called as snapdragon, dog flower, bunny rabbit or bunny mouth. Snapdragons are one of the most popular and widely grown garden annuals. It is ideally suited for beds, pot, edging, window boxes, herbaceous border and rock gardens. Tall cultivars can be used among the shrubs, at the background of the annuals like hollyhock, larkspur, etc. in mixed borders or with herbaceous plants. The intermediate cultivars are very useful for bedding and potting purposes. Both these types are excellent for cut flower production. The dwarf cultivars are good for edging and bordering formal beds. The dwarf hybrids are suitable for covering the patches in rock garden. They are used in floral arrangements and in bouquets too. Their production for cut flower purpose began with the introduction of a winter flowering cultivar Chevoit Maid, followed by several F₁ hybrids with desirable cut flower qualities. The F₁ hybrids are grown all the year round. Flowers have good keeping quality, as they remain fresh for 6-7 days. Snapdragon has also been reported to have medicinal importance. It has diuretic and astringent properties and have been employed for the treatment of scurvy, liver tumor and ulcers.

Abstract: Snapdragon, a decorative ornamental, is used as model plant for genetic and biochemical study. These are popular flowering potted plants, bedding plants and cut flowers around the world due to their flowering floriferousness, wide range in flower colour, size, and shape with numerous phenotypes (Tall Giant/ Grandiflora, Super Giant, Dwarf, Semi-dwarf, Miniature, etc.) series (Butterfly, Rocket Hybrid, Sweet Heart, Pixie, etc.) and cultivars available in market. Hybrid seed production transformed the crop; continued domestication by flower breeders produced a wide range of flower colours and flower patterns. The increasing knowledge of the inheritance of traits and molecular genetics techniques are valuable tools aiding modern snapdragon breeders. Snapdragons are of the few floriculture crops which have genetic evolutionary race history, precise elucidation of taxonomic relationships between taxa, genomic maps, and advanced molecular genetics. In particular elucidation of the genes involved in control of floral development and in anthocyanin biosynthesis pathway has enabled precision in the creation of new flower colours or modification of floral symmetry and expression.

Keywords: Antirrhinum, taxonomy, flower shape, structural genes, molecular biology.

Snapmelon [Cucumis melo L. var. momordica (Roxb.) Duthie * Fuller] originated  in India. It was intensively cultivated in the 19th century in Northern India (Duthie 1905) where it is commonly called as ‘Phut’ which means to split or crack. Immature fruits are cooked or pickled and the low sugared mature fruits are eaten raw. The mature fruits crack or burst. Fruit cracking is  either longitudinal or random starting in middle of fruit (Fig.1).

The North Eastern Region of India possesses unique potential for fishery activities. The region represents all agro-climatic zones ranging from warm water drainage system to cold water conditions facilitating freshwater fishing and is identified as the hot spot of freshwater biodiversity. So far about 267 fish species have been reported to be present in the region, which is approximately 33.13% of the total Indian fresh water fishes (Munilkumar and Nandeesha, 2007). The total land coverage of the region is 2.55 lakh sq. km. which is about 7.76% of the country, out of which 70% is hilly terrain (Mahanta and Tyagi, 2003). The main fishery resources of the region comprises of rivers (18,968 km), reservoirs (8,019 ha), beels/lakes (1,48,491 ha) and tanks and ponds (42,782 ha) (Ghosh and Ponniah, 2008).

The North Eastern Region of India with its large fish eating population, needs planned sustainable development of its existing as well as potential fishery resources. A challenging environment for fisheries development prevails in the region by way of very high demand and price of fish. Given the socio-economic conditions and vast fishery resources of the region, there is a strong chance for diversion of work force to productive sectors like fisheries thus transforming the economy of the region and further socio-economic development.

11.1. Definition

Jones: Variations or modifications of any aspect of social process, social patterns, social interaction or social organization.

Gillin and Gillin: Variations from the accepted modes of life; whether due to alteration in geographical conditions, in cultural equipment, composition on the population or ideologies and whether brought about by diffusion or inventions within the group.

Davis and Mac Iver: Change in the relationships.

ABSTRACT

Social primates appear to be knowledgeable about one another’s behaviour to different extents. But do they know as much about one another’s beliefs and intentions? Are they adept at recognizing the similarities and differences between their own and others’ states of mind?

Introduction
An animal’s asymmetry in aggression towards another species is commonly used to characterise its dominance. In other contexts, dominance describes people who emerge victorious from brief dyadic competitions. Most animal groups are arranged in a hierarchical fashion, whereby members at higher ranks have more access to resources and opportunity for procreation than members at lower ranks. Signals of Dominance: Acts or structures known as signals are employed by signalers to convey information to recipients in a way that elicits a response from them. This response usually has positive fitness consequences for both the signaler and the recipient. These signs don’t always have to be easy to see.
Communities vary in the hierarchical pattern of dominance. The most common kind of rank relationships are those in which there is a “alpha” who is better than all other members of the group, a “beta” who is better than all members except the “alpha,” and so on down the hierarchy to the lowest ranker who is under all others. Therefore, if powerful males may be arranged in a single sequence, the system is known as a simple and linear dominance hierarchy.
Concepts of Dominance Hierarchies
1. Establishing dominance
2. Maintaining dominance
Dominance Hierarchy Types
1. Statistical hierarchy
2. Confidence hierarchy
3. Assessment hierarchy

4.1 Research Setting

In any social science research, it is hardly possible to conceptualize and perceive the data and interpret the data more accurately until and unless a clear understanding of the characteristics in the area and attitude or the behavior of people is at commend of the interpreter who intends to unveil an understanding of the implication and behavioral complexes of the individual who live in the area under reference and form a representative part of the larger community. The socio-demographic background of the local people in a rural setting has been critically administered in this section. A research setting is a surrounding in which input and elements of research are contextually imbibed, interactive and mutually contributive to the system performance. Research setting is immensely important in the sense because it is characterizing and influencing the interplays of different factors and components.

The term “research setting” describes the specifics of the location where the study was carried out. The study area is typically a specific geographic area, such as a state, district, block, or gram panchayat area, chosen based on the investigator’s convenience and with suffice. The term research setting implies the specific details of the location where the study was carried out are referred to as the research context. Typically, the study area consists of a specific geographic area, such as a state, district, block, or gram panchayat, chosen based on the investigator’s convenience. The investigator should have sufficient knowledge of the area’s location, communication infrastructure, etc. to enable them to easily collect data from every corner of the area. Each setting” describes the specifics of the location where the study was carried out. The study area is typically a specific geographic area, such as a state, district, block, or gram panchayat area, chosen based on the investigator’s convenience and with sufficient knowledge of the area’s location, communication infrastructure, etc. to enable the investigator to easily approach every part of the area for data collection. The knowledge of the area’s location, communication infrastructure, etc. to enable the investigator to easily approach every part of the area for data collection.” describes the specifics of the location where the study was carried out. The study area is typically a specific geographic area, such as a state, district, block, or gram panchayat area, chosen based on the investigator’s convenience and with sufficient knowledge of the area’s location, communication infrastructure, etc. to enable the investigator to easily approach every part of the area for data collection. Because of the COVID-19 epidemic, the majority of the data collection for this study was conducted over the phone in accordance with the interview schedule. In order to easily comprehend the people’s knowledge, attitudes, and behaviours, investigators also need to have a fundamental awareness of their sociodemographic background. A research setting is an environment where research components and inputs are interwoven, contextualized, and mutually enhance system performance. The research setting has a crucial role in describing and affecting the interactions between various components and elements. The idea behind this kind of presentation is to absorb the study environment in terms of wider

4.1 Research Setting

In any social science research, it is hardly possible to conceptualize and perceive the data and interpret the data more accurately until and unless a clear understanding of the characteristics in the area and attitude or the behavior of people is at commending by the interpreter who intends to unveil an understanding of the implication and behavioral complexes of the individual who lives in the area under reference and form a representative part of the larger community. The socio-demographic background of the local people in a rural setting has been critically administered in this section. A research setting is a surrounding in which input and elements of research are contextually imbibed, interactive, and mutually contributive to the system performance. The research setting is immensely important in the sense because it is characterizing and influencing the interplays of different factors and components.

Research setting refers to the detail information of an area where the study has been conducted. The study area, generally comprises of a particular geographical area viz. a state, district, block, or gram panchayat area selected according to the convenience of the investigator who possesses adequate knowledge regarding the location, communication facility etc. of the locality so that he/she can easily approach each and every corner of the area for data collection. Here. in this study the data collection was done mostly over telephone based on the interview schedule due to Covid-19 pandemic situation. Besides the investigators must also have the basic knowledge about the socio demographic background of the people so as to have an easy understanding of their knowledge, attitude and behavior. 

The research setting provides specific details about the location where a study is conducted. This study area typically encompasses a particular geographical region, such as a state, district, block, or gram panchayat, chosen according to the research requirements. The researcher must have a thorough understanding of the locality, including its communication methods, in order to effectively access all parts of the region for data collection.

In social science research, a clear comprehension of the characteristics, attitudes, and behaviours of the individuals within the study area is essential. Without this understanding, accurately conceptualizing, perceiving, and interpreting data becomes challenging. To obtain a comprehensive understanding of the implications and behavioural intricacies of the local people representing a broader community in the referenced study area, researchers must have a solid grasp of these factors. Therefore, this chapter critically analyses the socio-demographic background of the residents in a rural setting.

The term “research setting” denotes the context in which research inputs and elements are absorbed, interacted with, and mutually contribute to the system’s overall performance.

The research setting is crucial because it shapes and influences the interactions of various factors and components. Therefore, conducting a study on how farmers perceive persuasive issues and other topics requires a local context that takes into account the unique natural environment, demographics, crop ecology, institutional framework, and socio-cultural factors. For example, when writing a paper about the social behaviour of chimpanzees, it is important to include details about the research setting. This may include information such as where the chimpanzees were studied (in the wild or in captivity), the number of chimpanzees that were observed, whether they were part of the same social group, the geographic location, the time of the study, the season/weather conditions, the availability of resources such as food, water, and shelter, and any environmental factors that were present. There are two types of research settings: macro and micro. The macro research setting encompasses the entire state, while the micro research setting focuses on specific districts, blocks, or village peripheries. The aim of this approach is to understand the study environment from broader perspectives using the state as a reference frame and the district and block profiles as units of in-depth analysis.

The research setting provides specific details about the location where a study is conducted. This study area typically encompasses a particular geographical region, such as a state, district, block, or gram panchayat, chosen according to the research requirements. The researcher must have a thorough understanding of the locality, including its communication methods, in order to effectively access all parts of the region for data collection.

In social science research, a clear comprehension of the characteristics, attitudes, and behaviours of the individuals within the study area is essential. Without this understanding, accurately conceptualizing, perceiving, and interpreting data becomes challenging. To obtain a comprehensive understanding of the implications and behavioural intricacies of the local people representing a broader community in the referenced study area, researchers must have a solid grasp of these factors. Therefore, this chapter critically analyses the socio-demographic background of the residents in a rural setting.

The term “research setting” denotes the context in which research inputs and elements are absorbed, interacted with, and mutually contribute to the system’s overall performance.

The research setting is crucial because it shapes and influences the interactions of various factors and components. Therefore, conducting a study on how farmers perceive persuasive issues and other topics requires a local context that takes into account the unique natural environment, demographics, crop ecology, institutional framework, and socio-cultural factors. For example, when writing a paper about the social behaviour of chimpanzees, it is important to include details about the research setting. This may include information such as where the chimpanzees were studied (in the wild or in captivity), the number of chimpanzees that were observed, whether they were part of the same social group, the geographic location, the time of the study, the season/weather conditions, the availability of resources such as food, water, and shelter, and any environmental factors that were present.