eChapters

3.1 Soil Inhabiting Fungi

There’s a wild and wonderful world that remains hidden for most of us, at least most of the time. It’s an amazing ecosystem filled with fascinating creatures interacting with one another to create an intricate, dynamic web of life. It’s right under our feet: the soil ecosystem! Many organisms make up this ecosystem, and some of the most important ones are the fungi. Healthy soil is alive and teeming with an array of fungus species, each playing a vital role in its environment. Healthy soils are alive with an especially diverse array of fungal species, and many are essential to the health of the plants growing in that soil. In fact, a soil devoid of fungi is a dead soil, and is unlikely to support thriving plants. Some soil fungi are single-celled and visible only through a microscope. Others form large, underground networks of filaments that can cover an area the size of a football field or larger. Most of us are familiar with the above-ground parts of some soil fungi, the mushroom.

Fungi are one of the key microbial groups in terrestrial ecosystems that enabled colonization of land by plants and facilitated development of soil that supports most of the biota on Earth. The kingdom Fungi is one of the most diverse groups of life with an estimated 1.5–6 million species that represent heterotrophic mutualists, pathogens, and saprotrophs (Tedersoo et al., 2017). The 70,000–100,000 currently recognized species are distributed among 156 orders, 46 classes, and 12 phyla. Fungi have traditionally been identified and classified based on morphological characters of fruiting bodies and living cultures. Similar to bacteria and archaea, merely <1% of fungal species have been cultivated with established protocols, which renders large taxonomic groups undescribed and virtually unknown to science. Roughly 80% of all soil-inhabiting fungal taxa cannot be identified at the species level, and 20% cannot be reliably assigned to known orders.

Biological control is defined broadly as the “use of natural or modified organisms, genes, or gene products” to reduce the effects of pests and diseases. The many approaches to biological control can be categorized conventionally into regulation of the pest population (the classical approach); exclusionary systems of protection (a living barrier of microorganisms on the plant or animal that deters infection or pest attack) and systems of self-defense (resistance and immunization) (Anchal Sharma et al., 2013). The agents of biological control include the pest- or disease-agent itself (sterile males or a virulent strain of pathogens), antagonists or natural enemies, or the plant or animal managed or manipulated (immunized) to defend itself. Principles of plant health care are offered, know the production limits of the agro-ecosystem, rotate the crops, maintain soil organic master, use clean planting material, plant well-adapted, pest resistant cultivars, minimize environmental and nutritional stresses, maximize the effects of beneficial organisms and protect with pesticides as necessary.

Biological control is the control of one organism by another. This control may be expressed as either a longer population of the pest or as a restriction or prevention of the severity or incidence of pest damage without regard to the pest population (Cook and Baker, 1983). Biological control depends on knowledge of biological interactions at the ecosystem, organism, cellular, and molecular levers and often is more complicated to manage compared with physical and chemical methods. Biological control is also likely to be less spectacular than most physical or chemical controls but is usually also more stable and longer lasting. In spite of biological controls having been used in agriculture for centuries, as an industry biological control is still in its infancy. Biological control is now being considered for an increasing number of crops and managed ecosystems as the primary method of pest control. One reason for its growing popularity is its record of safety during the past 100 years considered as the era of modem biological control (Anchal Sharma et al., 2013). No microorganism or beneficial insect deliberately introduced or manipulated for biological control purposes has, itself, become a pest so far as can be determined, and there is no evidence so far of measurable or even negligible negative effects of biocontrol agents on the environment. The new tools of recombinant DNA technology, mathematical modeling, and computer technology combined with a continuation of the more classical approaches such as importation and release of natural enemies and improved germplasm, breeding, and field testing should quickly move bio-control research and technology into a new era.

5.1 Important Terms

i. Inoculum: The infective pathogen propagules coming in contact with the host constitutes the inoculum. The inoculum in the liquid state is a significant factor in anaerobic digestion in solid phase because it is very useful to convey the micro organisms, the water of recirculation. Depending on the particular inoculant formulation, the inocula can be used for seed coating, for dipping seedlings, direct application to the furrow, or as foliar application. An appropriate inoculum consists of copious amounts of active microbes having the potential to convert the organic matter to biogas and the S/I ratio is essential for the rate of degradation of a recalcitrant substrate since it governs not only the biogas composition, digestion period and reactor. Spread of inoculum may occur by wind, water, infected plant material, insects, animals, birds, and people. Plant diseases may have more than one source of inoculum. The infection cycle of some economically important soil-borne plant pathogens involves a combination of primary infection from particulate inoculum residing in the soil and secondary infection as disease is spread from infected to susceptible hosts.

The infectivity of inoculum can be quantified by the pathozone profile which measures changes in the probability of infection when inoculum occurs at different distances from the host. For instance, the germinability of inoculum, the growth of the mycelial colony and the infectivity of mycelium at the surface of the host combine to dictate the shape of the pathozone profile for Rhizoctonia solani on radish. The ultimate shape of the pathozone depended on inoculum type and was particularly sensitive to changes in the density and distribution of the mycelium in the fungal colony. Mycelium from an infected radish plant grew much further and at a higher density than that from particulate inoculum (mycelial discs). This results in pathozone profiles that differed in shape. For particulate inoculum the profile rise and fall with distance whilst for an infected plant the decay is sigmoidal.

6.1 Competition

Soil microorganisms in particular are perceived as active competitors that have evolved diverse strategies to facilitate resource acquisition. Activities including motility, coordinated behavior, and antibiotic production can tip the competitive balance, resulting in numerical dominance or local extinction of competing populations. Functional consequences of microbial social behaviors have been studied extensively and demonstrate the importance of factors such as relatedness, kin discrimination, enforcement of cooperation, and competition among relatives to microbial survival and f itness in the environment (Adil Essarioui et al., 2017). However, most investigations have focused on interactions among closely related taxa, often among species or genera. Yet, in natural environments, coexistence of individuals from diverse microbial phyla and kingdoms is common. In particular, bacteria and fungi commonly coexist in soil, but there has been relatively little study of the role of species interactions in mediating the dynamics of specific bacterial and fungal populations in soil. Moreover, we have little understanding of the extent to which the ecological context, and specifically plant host or plant community diversity, may influence bacterialfungal interactions in soil. Such studies are needed to begin to establish a more complete understanding of the ecological and coevolutionary dynamics of soil microbial populations.

Microbes have coevolved to engage in complex networks of interactions with coexisting kin and non-kin individuals in the soil and in association with plants. Microbial antagonism and resource competition within complex communities have been the focus of many studies that have explored the effects of diverse factors on the ecological outcomes of these interactions. However, the concurrent impacts on these processes of plant species richness and plant host, which jointly structure the environment within which rhizosphere microbes interact, have received far less attention. This is despite the fact that both plant community richness and plant species have been shown to impact microbial community composition and function in rhizosphere soil, with potential implications for microbial interactions and pathogen suppression in natural and agricultural habitats.

7.1 Conducive Soils

Without a conducive environment, plant disease does not occur. Soils that favour the disease/ and the pathogen are generally referred to as conducive soils. Inoculum of powdery scab is the either the spore ball (an aggregation of thick walled, tough, resting spores, comprising an average of 700 spores) or the swimming spore (zoospore) that each spore of the spore ball releases. Spore balls of powdery scab have been shown to persist for long periods (Brierley et al., 2008). Exactly, how long they can survive has not been fully determined, but experimentally and anecdotally, it is much longer than a typical rotation. Inoculum may be seed-borne or soil-borne and whatever the source spore balls are able to cause infection and disease. Seed tubers may carry spore balls within powdery scab lesions or may carry spore balls symptomlessly where they have been picked up from adjacent infected tubers or contaminated machinery (e.g. on grading lines). In addition, recently, it has been found that tubers may be latently infected. That is where tubers are infected but symptoms are not expressed. Latent infections may be associated with conditions that are unfavourable for disease development, such as sub-optimal temperatures.

i. Soil Moisture: A high soil moisture content both encourages swimming spore release and facilitates movement to the host. It is generally accepted that swimming spores are unable to move through the soil without free water within the soil matrix (i.e. soil saturation). Many studies confirm the importance of free water in soil as a requirement for infection. The occurrence of wet soil conditions prior to tuber initiation, enabling inoculum multiplication, has been cited as important for high levels of powdery scab. Alternatively, prolonged wet soil conditions after tuber initiation can lead to high levels. In experiments investigating soil moisture, there is disagreement over the importance of constant versus fluctuating soil moisture conditions in powdery scab development. However, it is difficult to make clear comparisons because soil moisture levels have not always been measured and factors that may affect disease development (e.g. soil type, initial inoculum level) will have differed from experiment to experiment. Some studies have shown that constant high soil moisture has suppressed powdery scab development possibly due to low oxygen/high carbon dioxide levels rendering swimming spores inactive.

Introduction

Entrepreneurial communication is an action intended to forge a relationship with the other party in order to affect their interest, attitude, and behavior. This is due to the fact that it is never done without considering how it would affect both qualitative and quantitative outcomes. A person can transmit or receive information about another person’s needs, wants, perceptions, knowledge, or emotional states through the act of communicating. In the context of entrepreneurship, communication refers to a set of procedures for exchanging knowledge and understandings between individuals who are engaged in a predetermined or novel situation.

Every interaction that takes place during communication involves a shift and is dynamic. Since it is dependent on interaction and a transaction between speakers, communication cannot be understood s a straightforward process of transmission. The planned actions and activities are not hindered because the emission and reception occur simultaneously, with h the transmitter acting as both a receiver and a transmitter. The process of sending and receiving signals as knowledge, feelings, emotions, skills, talents, attitudes, activities, etc. is known as entrepreneurial communication.

In terms of information sharing about events, situations, involvement, impact, adaptation, etc., it is built on interactions between business owners, educators, and educated youth.

Concept of Review of Literatures

The Review of literature is a systematic, explicit, and reproducible method for identifying, evaluating, and synthesizing the existing body of completed and recorded work produced by researchers, scholars, and practitioners. The Review of literature is also a resource paper, which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic. These are available mostly in academic and scholastic journals.

Review of literature provide the basics for research in nearly every academic f ield. The aim of review of literature is to highlight what has been done so far in the field of interest and how our findings are related to earlier research. The review of literature also indicates the following by providing referential inputs.

(i) Approaches

(ii) Methods

(iii) Variables used

(iv) Statistical procedure

(v) Expected results

(vi) Provides theoretical background to our study.

(vii) Helps justify how our findings are related to our body of knowledge in our field of research.

(viii) Establishes a link between what we propose to study and what has already been found. It helps us to refine our research methodology.

Entrepreneurship: the Concept and Definitions

Entrepreneurship is the capability to improve, arrange and continue a business enterprise, along with any of its uncertainties to make a profit. We can say an example of entrepreneurship is the starting of a new business, a new venture with some challenges and specific objectives.

Meaning of Entrepreneur

An entrepreneur is defined as one person who has the ability and desire to establish, administer and succeed in a startup venture along with the risk entitled to it, to make profits. The best example of entrepreneurship is the starting of a new business venture. Entrepreneurs are often known as a source of new ideas or innovators and bring new ideas in the market by replacing old ones with a new invention.

According to Cole (1949), an Entrepreneur represents an individual or a group of individuals, who conceive, initiate and maintain for a sufficiently long period a social institution which produces economic goods or to put it differently.

Communication: Communication is an act by which one person gives to or receives from another person, the information about the person’s need, desires and perceptions. Knowledge or affective states: Communication is an act by which one person gives to or receives from another person, the information about the person’s need, desires, and perceptions. Knowledge or affective states.

Entrepreneurial Communication: It should have some unique features. The way one teacher talk with a student, the way one official personnel talk with an individual, like them one entrepreneur should communicate with their customer to uplift of their enterprise. So this type of communication differs from the general communication.

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 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 physical, social, or experimental context in which research is carried out is referred to as the research setting. This context must be accurately described in a study publication because it may have a significant impact on the findings and how they are interpreted. For instance, in a paper describing the social behavior of chimpanzees, the authors may need to provide the following information about the research environment: where the chimpanzees were observed (in the wild or in captivity), the number of chimpanzees observed, and whether they belonged to the same social group, the geographic location, the time of study, the season/weather conditions, the availability of resources like food/water/shelter, and the presence of environmental factor.

Area of the Study

The present study was taken up in West Bengal. From West Bengal, District Uttar Diaper, Blocks Kaliyaganj, Villages Radhikapur was selected.

Research methodology is a detailed plan of investigation and the blue print of procedure for carrying out the research. In this chapter, discussion on the methodology has been made to understand the concepts, methods and techniques, which are utilized to design the study, collect information, analyzing data and interpreting the findings for revelation of truth and formulation of theories. The entire chapter has been broken up under following sub-heads for easy understanding:

1. Locale of research

2. Sampling design

3. Pilot study

4. Variables and their measurements

5. Methods of data collection

6. Statistical tools used for analysis of data

Locale of Research

The present study has been conducted in a INDIA-BANGLADESH cross border village named Radhikapur in the state West Bengal. Villages from Kaliyaganj block in Uttar Dinajpur District.

The characters and the factors under study have been well discernible to this area

• The researcher’s close familiarity with respect to area, people, officials and local dialects

• The highly cooperative and responsive respondents

• The profuse scope to get relevant information regarding entrepreneurship communication behavior, economical communication, information seeking & responding behavior, information flow in & flow out etc.

• The locale is located at the terminal point & beside the INDIA BANGLADESH border, so there is some cross border impact also.

Results and Discussion:

Concept Result is the outcome, consequences or conclusion of a problem, probe or experiment organized after a period of time. This conclusion can be one result, multiple results or no result as such. The length of time taken to find a result can vary from less than a second to many years. In this chapter the result of the Research has been elaborated and also discussed later.

The purpose of the discussion/revelation is to interpret and describe the significance of our findings in light of what was already known about the research problem being investigated, and to explain any new understanding or insights about the problem, after we have taken the findings into consideration. The discussion will always connect to the introduction by way of the research questions or hypothesis we posed and the literature we reviewed, but it does not simply repeat or rearrange the introduction and the discussion always explain how our study has moved towards the research problem.

This table presents the distribution of 19 independent variables(x1-x19) and 6 dependent variables (y1-y6) in terms of their Minimum, Maximum, Mean, Variance, Standard deviation, and Coefficient of variation.

Here, it is depicted that the average age (x1) of the respondents is 50.307. The C.V. value for the variable is 18.521. So, it indicates that the distribution of the variable is highly consistent.

From the table it is depicted that the average education (x2) of the respondents is 7.600. So, almost on an average the individual education is 8 for every respondent. The C.V. value for the variable is 41.553. So, it indicates that the distribution of the variable is fairly consistent.

Recommendations

Based on the empirical research, following recommendations can be made for this specific area of research:

(i) Land size based planning for business communication can help the growth and success of farm enterprise.

(ii) Rice based farming system, supported by irrigation is offering a unique opportunity for capacity building of the farmers of West Bengal.

(iii) Training, focusing on business communication, handling ICT tools and mobile telephony, can go a long way for making communication behavior more adaptive to present social ecology of agriculture and allied sectors of West Bengal.

(iv) Social capitals like, Schools, Panchayat, Credit organizations, Market linked institutions, are to be integrated for shaping up a new form of Entrepreneurial communication behavior.

Limitations: The most important limitations which have been observed in this research are as follows:

Future Scope of the Research

The present study has been conducted by driving the insights deeper into the nature, intensity and character of the problems creating barrier against the Entrepreneurial communication. Entrepreneurial communication nowadays is a need in these days of unemployment and stands to be both the means and method of sustaining life process in terms both assets and capital, it needs more comprehensive study. Attaining Entrepreneurial communication among the upcoming and motivating entrepreneurs, anywhere is an endless process by itself. The present study thus leaves behind the following domains to be researched out in future:

The study can be extrapolated to other domains of entrepreneurship.

1) Modeling of Entrepreneurial communication including the positive motivation, can be achieved through further studies.

2) The future study of this particular topic has a scope to include several contextual and realistic variables other than the variables included in this study.

3) The structure and the function of Entrepreneurial communication behavior and process, can well be understood from further study of the similar topic.

4) There is a scope of methodological innovation in future and application of artificial intelligence in this study

5) Policy research on Entrepreneurship and Entrepreneurial communication as to monitor or rationalize the magnitude of rural entrepreneurship, for keeping the pace of growth unabated can be achieved.

The present research had been conducted to study the Entrepreneurial communication and the process, factors and impact in Agricultural enterprise and allied sectors of selected block of West Bengal and in the end the comparison is made. The study had been conducted at villages Radhikapur from blocks Kaliyaganj of West Bengal. A pilot study was conducted to understand the area, its people, institution, communication and extension system of these states.

An exhaustive list of respondents was prepared critically with the help of some villagers. From the list, 75 respondents from the village were selected for the study through Systematic Random sampling method. The primary data were collected with the help of structured interview schedule by following the personal interview method. The secondary data were collected from our departmental library, internet, Department of Agriculture, West Bengal, Bidhan Chandra krishi Viswavidyalaya, etc. for establishing the conceptual framework of the study.

The general objective of the study is to estimate and analyze the “Entrepreneurial communication: The process, factors and impact in Agricultural enterprise and allied sectors of selected block of West Bengal” and the specific objectives are:

1) To study the present status of the entrepreneurial communication.

2) To measure the unique features entrepreneurial communication over the general communication.

3) To generate micro level policy implementation based on the empirical research.

4) To estimate intra and inter level of interaction among dependent variable and independent variable.

5) To isolate factors impactions on Entrepreneurial behavior.

7.1: Summary

19 Independent variables and 6 Dependent variables were selected for the study respectively and measured with the help of exact scales developed by previous social science researchers or by modifying the developed scale by structured interview schedule for requirement of the study.

Independent variables selected for the study are, Age (x1), Education (x2), No. of enterprise (x3), Year of enterprise (x4), Family size (x5),Average Family education (x6), Material possessed (x7), Size of land holding (x8), Size of homestead land (x9) No. of fragments (x10), Crop yield (x11), Cropping intensity (x12), Annual Income (x13), Family expenditure (x14), Marketed surplus (x15), Marketable surplus (x16), Family labor (x17), No. of male workers (x18) and No. of female workers (x19). The Dependent variables selected for the study are, cosmopo lite Farm enterprise information (y1), localite Farm enterprise information (y2), Information seeking and responding behavior (y3), Entrepreneurial communication behavior (y4), Economical communication (y5) and Transportation cost (y6).

Indian agriculture now stands at a cross road. By 2050, Indian population will overtake that of China’s. The world population in the same year will be close to 9.5 billion. And to feed the human population of this planet, the agricultural production needs to be increased 60% over the present one by 2050. For India the target is 450 million tons by 2050.

This is a humongous task. This mammoth escalation of targeted food production has to be carried out with the constraints and barrier created by climate change, erosion of soil, bio-diversity, ecological disruption due to mindless anthropogenic action and wrong planning.

The production, productivity, income, livelihood, and ecological resilience in agriculture are not performing in perfect orchestration. They are in apparent contradiction. To produce 1 kilogram of rice, the equivalent water foot print is about 4000 litres. It is obvious that enhancing food productivity, there could be more disruption and stress on soil, water and bio-diversity. The ecological resilience is a subject of musical chaos and symphony amidst ecological function-stress-conservation-extraction-. Without depletion and disruption, it is simply impossible to initiate and foster agriculture production as well as productivity. But the question is what could be level of endurance? Wherein restoration and retention, ecological resilience will move in resonance and complementary manner.

Concept of Review of Literatures

The Review of literature is a systematic, explicit, and reproducible method for identifying, evaluating, and synthesizing the existing body of completed and recorded work produced by researchers, scholars, and practitioners. The Review of literature is also a resource paper, which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic. These are available mostly in academic and scholastic journals.

Review of literature provides the basics for research in nearly every academic f ield. The aim of review of literature is to highlight what has been done so far in the field of interest and how our findings are related to earlier research. The review of literature also indicates the following by providing referential inputs.

(i) Approaches

(ii) Methods

(iii) Variables used

(iv) Statistical procedure

(v) Expected results

It is the scholastic and theoretical exercise that configures the operational definition and text of entire research work. The conceptual inputs, axiomatic inputs, logic of discourses and the pursuit knowledge come together to frame the theory in compliance and in congruence with the set of objectives and research designs spelt out in the research process.

3.1 Definition of Farmer, Farm, and Farming System

A farmer is a person engaged in agriculture, raising living organisms for food or raw materials. The term usually applies to people who do some combination of raising field crops, orchards, vineyards, poultry, or other livestock. A farmer might own the farm land or might work as a laborer on land owned by others. In most developed economies, a “farmer” is usually a farm owner (landowner), while employees of the farm are known as farm workers (or farmhands). However, in other older definitions a farmer was a person who promotes or improves the growth of plants, land or crops or raises animals (as livestock or f ish) by labor and attention. Over half a billion farmers are smallholders, most of whom are in developing countries, and who economically support almost two billion people. Globally, women constitute more than 40% of agricultural employees.

A farm is an area of land where livestock (animals) are raised and crops (plants) are grown for use as food, fiber, and fuel. The people who own and work on the farm are called farmers.

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 physical, social, or experimental context in which research is carried out is referred to as the research setting. This context must be accurately described in a study publication because it may have a significant impact on the findings and how they are interpreted. For instance, in a paper describing the social behavior of chimpanzees, the authors may need to provide the following information about the research environment: where the chimpanzees were observed (in the wild or in captivity), the number of chimpanzees observed, and whether they belonged to the same social group, the geographic location, the time of study, the season/weather conditions, the availability of resources like food/water/shelter, and the presence of environmental factor.

Research methodology is a detailed plan of investigation and the blue print of procedure for carrying out the research. In this chapter, discussion on the methodology has been made to understand the concepts, methods and techniques, which are utilized to design the study, collect information, analyzing data and interpreting the findings for revelation of truth and formulation of theories. The entire chapter has been broken up under following sub-heads for easy understanding:

1. Locale of research

2. Sampling design

3. Pilot study

4. Variables and their measurements

5. Methods of data collection

6. Statistical tools used for analysis of data

5.1: Locale of research

The present study has been conducted in a INDIA-BANGLADESH cross border village named Mitrapur in the state West Bengal. Villages from Haringhata block in Nadia District.

Results and discussion: concept Result is the outcome, consequences or conclusion of a problem, probe or experiment organized after a period of time. This conclusion can be one result, multiple results or no result as such. The length of time taken to find a result can vary from less than a second to many years. In this chapter, the result of the Research has been elaborated and also discussed later. The purpose of the discussion/revelation is to interpret and describe the significance of our findings in light of what was already known about the research problem being investigated, and to explain any new understanding or insights about the problem after we have taken the findings into consideration. The discussion will always connect to the introduction by way of the research questions or hypothesis we posed and the literature we reviewed, but it does not simply repeat or rearrange the introduction and the discussion always explain how our study has moved towards the research problem.

7.1 Summary

The presentre search hadbeenconducted to study the Entrepreneurial communication and the process, factors and impactin Agricultural enterprise and allied sectors of selected block of West Bengal and in the end the comparison is made. The study had been conducted at villages Mitrapur from blocks Haringhata of West Bengal. A pilot study was conducted to understand the area, its people, institution, communication and extension system of these states.

An exhaustive list of respondents was prepared critically with the help of some villagers. From the list, 75 respondents from the village were selected for the study through Systematic Random sampling method.The primary data were collected with the help of structured interview schedule by following the personal interview method. The secondary data were collected from our departmental library, internet, Department of Agriculture, West Bengal, Bidhan Chandra Krishi Viswavidyalaya etc. for establishing the conceptual framework of the study.

The general objective of the study is to estimate and analyse the “Productivity, Income, Livelihood and Ecology: The resilience analysis in Argo ecosystem” and the specific objectives are

• To study the present statuses of 1. Income 2. Productivity 3. Livelihood and 4. Ecological resilience of the respondence under study in a selected locale.

• To estimate the intra and inter level interaction among and between the selected sets of variables to estimate the common point of the interaction of the ‘Y’ Protected characteristics.

• To generate micro sociological policy implication based on empirical evidence.

• To isolate factors impactions on ecological resilience.

1. The selection of more number of relevance variables could have added better understanding and comprehensive of the research.

2. Mathematical optimization and simulations could have been much effective in integrating as well as co-integrates the apparently different aspect of yield, income, livelihood and ecological resilience in the form of a common valley of management of a land.

3. Application of ARIMA (Autoregressive Integrated Moving average) and SEM (structural equation modeling) as instruments of interpretation and analysis can be more effective.

4. Ecological resilience metritis more active and dummy variable including outliers can be future research towards modelling with hard evidences

5. A pull of chronological data distribution over 30 years can undergo simulation and decision ecology for promulgating micro sociological policy and application.

6. Social resilience has been the predicament for perceiving ecology resilience and organic diode can help to make the entire thing strongly place on the foundation of ecological research at least.

In this chapter, the importance of seafood in terms of their nutrition, and different methods of processing are dealt. Seafood quality and safety terminologies are explained briefly. The quality parameters affected by rigor mortis in raw, iced and cooked fish are given. Phenomenon of gaping described with reference to rigor mortis. Quality dimension of seafood is explained with intrinsic and extrinsic parameters. Various intrinsic factors affecting seafood quality such as f ish species, seasonal changes, parasite infestation and capture conditions are discussed in detail. The next part elucidates the sensory parameters affecting the seafood quality describing the objective and subjective method of quality assessments. Objective method covers both descriptive and discriminative tests. The final part mentions the Codex guidelines available for the conduction of seafood sensory assessment. At the end, the reader gains the knowledge on the basic information about seafood, role of rigor mortis in affecting seafood quality and the sensory quality assessment methods.

Objective

To learn the nutritional importance of seafood and their processing; rigor mortis and their role in seafood quality, intrinsic and extrinsic factors affecting seafood quality and sensory quality assessment methods.

1.1. Importance of Seafood

Seafood has been traditionally a part of diet in many parts of the world. In some countries like India, it constitutes the main supply of animal protein among coastal population. Seafood is a low-calorie food and easily digestible compared to other protein-rich meat and poultry products and hence, it is a good choice for elderly persons to obtain their daily protein requirements. Seafood has high-quality quality enriched with all the essential amino acids required for human health. It provides about 1/3rd of the average recommended daily allowance (RDA) of protein.

Introduction

Quality of fish is affected by various factors, which are classified into two categories: intrinsic factors and extrinsic factors. Intrinsic factors are the chemical and physical properties inherent to fish. Extrinsic factors are treatments given to fish before and after catch until it reaches the consumer, which includes the method of catch, cross contamination, processing, preservation, and product storage environment (temperature, humidity, packaging). The processing methods such as drying, smoking, chilling, and salting greatly help to minimize the spoilage. The quality of fish is also dependent on cold chain, in which the temperature is managed and monitored at every stage of production, transport, storage and sale.

2.1. Pre-Harvest Factors

Pre-harvest factors relates to the intrinsic factors affecting the quality of fish, as they are beyond the direct control of human. Various intrinsic factors affecting quality are fish species, size, sex, physiological state, parasites, naturally toxic fish, pollutants, and occasional peculiarities. Additionally, some of the extrinsic factors like method of catch and feeding interruption for starvation are also considered as pre-harvest factors affecting the quality of fish.

2.1.1. Species Characteristics

The quality of fish is related to species. For instance, flat fish keep better than round fish. Post-mortem pH varies between species. For example, long rigor period and low pH (5.4-5.6) of very large flatfish and halibut give relatively long iced storage life of 21 days, while mackerel with low post-mortem pH has no effect on shelf life. Some fish are rated as good quality as they are expensive, example, seer fish and pomfret. Fatty fish are rejected sensorial before lean fish due to the appearance of oxidative rancidity. So, lean fish keep longer than fatty fish under aerobic storage. Bony fish are edible longer than cartilaginous fish. Skin of fatty pelagic fish is very thin and contribute to faster

spoilage rate, as it allows enzymes and bacteria to penetrate more rapidly. Thick skin and slime of flatfish contribute for better keepability, as slime contains bacteriolytic enzymes, antibodies and other antibacterial substances.

Introduction

Seafood undergoes rapid spoilage after capture or harvest due to their highly perishable nature. Spoilage refers to any change that renders seafood unacceptable for human consumption. Spoilage occurs as a consequence of various microbial, biochemical and chemical breakdown processes. Spoilage leads to quality changes in seafood. Quality change refers to any change that occur after harvest due to unpredictable catch, uncontrolled harvest, inadequate handling, processing and storage facilities. The initial quality loss is mainly due to the post-mortem autolytic activity (enzymatic process) and chemical degradation process (lipid oxidation); and later by microbial degradation. The quality problems occur as a result of poor-quality raw material, ice and water, microbiological contamination, presence of heavy metals and other storage aspects during processing.

Processing of fish means preparing raw fish into a marketable form. Pre processing is done prior to final processing. Pre-processing is often done on board fishing vessel or in a shore based plant. It includes operation such as washing, sorting, grading, butchering, etc of the harvested fish. The butchering involves removal of non-edible portions such as viscera, head, tails and fins from fish. The yield of fish meat varies from 30 to 70% depending on the butchering process. Butchering process includes beheading, gutting, filleting, peeling, deveining, shucking, etc. The discarded portion of fish meat are fish wastes, often used for animal feed or for conversion to bioactive functional foods. Final processing of fish includes processes such as heating, freezing, drying, salting, marinading, irradiation, or addition of chemicals. The processed seafood is categorized into five major groups – chilled, frozen, canned, cured and other value-added products in this chapter.

Introduction

“Quality” refers to the aesthetic appearance and freshness of fish. It also involves safety aspects such as being free from harmful bacteria, parasites or chemicals. The best quality fish is the one consumed within the first few hours after postmortem. We studied in our previous chapters that in some instances, even very fresh fish in rigor mortis are unsuitable for filleting. So, slightly older fish in post-rigor are more desirable for the processors.

The assessment methods of fish quality are divided into sensory, instrumental, chemical and microbiological. Sensory method is superior and all other methods must correlate with the results of sensory evaluation. So, sensory method must be done more scientifically under controlled conditions without the effects of test environment, personal bias, etc.

4.1. Sensory Methods

Sensory evaluation is defined as the scientific discipline used to evoke, measure, analyze and interpret reactions characteristics of fish, as perceived through the senses of sight, smell, taste, touch and hearing. There are few instruments capable of measuring sensory profile viz. Instron for texture, electronic nose for odour, microscopic imaging for structure, etc.

In sensory evaluation, appearance, odour, flavour and texture of fish are evaluated by the human senses. The process involves three steps: (1) detection of a stimulus by the human sense organs, (2) evaluation and interpretation by a mental process; and (3) the response of the assessor to the stimuli. The response of stimuli varies among individuals e.g. some people cannot taste rancid flavour and some have low response to cold-storage flavour.

Introduction

Quality is very important in any production and operation system. It ensures whether the products produced or the services provided are of the right quality in right quantity at right time. Quality management must ensure proper quality of the product to survive in the market and expand its market. Quality of the product must be given importance to avoid quality failures that cause serious human inconveniences and wastage of money.

5.1. Definitions and Terminologies

5.1.1. Quality

We say a product is of satisfactory quality, if it satisfies the consumers. According to C. D. Lewis, a British writer, quality is “an asset which is offered to the potential customer of that product or service”. The International Organization for Standardization (ISO) has put up a more comprehensive definition of quality as “the degree to which a set of inherent characteristics fulfils requirements” (ISO 9000: 2005 – 3.1.1). In general terms, ‘quality’ is defined as the composite of characteristics that differentiate individual units of a product to determine its acceptability by the customer. Quality characteristics are nothing but elements that makes a product fit for use. Quality characteristics are further classified into categories called as parameters.

5.1.2. Total Quality Management

Total Quality Management (TQM) is an organization’s management approach, centered on quality. It improves the effectiveness and flexibility of a company or an organization. TQM is defined as “the system of establishing defect prevention actions and attitudes with a company or an organization on a permanent basis for the purpose of assuring conforming products or services directed at customer satisfaction”. TQM is based on the participation of all its members in decision making, which is aimed for long-term success, through customer satisfaction and benefits to the members of the company or organization and to the society.

Application of HACCP concept in surveillance & quality assurance programs for raw, frozen, canned, cured, irradiated, cooked, chilled, MAP & freeze dried products.

HACCP

Hazard analysis and critical control point (HACCP) is a system that identify, evaluate and control hazards that are significant for food safety (CAC, 2003). It is a science based systematic approach that assesses hazards and establishes control systems to focus on prevention rather than end product testing. It enhances the safety of the product from biological, chemical, and physical hazards in a production process. It provides way to demonstrate competence to consumers and compliance with legislative requirements.

6.1. History

HACCP was originally developed by Pillsbury Company in 1959 to produce zero defect food for astronauts of National Aeronautics Space Administration (NASA) in USA. In 1971, the HACCP concept was presented at the United States National Conference on Food Protection. The first major document on HACCP was approved by the National Advisory Committee on Microbiological Criteria for Foods (NACMCF) in 1989. The Codex then issued the first HACCP guidelines in 1993, which was adopted by the FAO/WHO Codex Alimentarius Commission (CAC). The USFDA’s Seafood HAACP program became mandatory in USA since 1997. The European Union, in 2004, laid down the general hygiene requirements of all food business operators (EC Regulation 852/2004) and the additional specific requirements for foods of animal origin, including live bivalve mollusks and fishery products which (Regulation EC 853/2004). The United States Food Safety Modernization Act 2011 became the latest enforcement of food safety measures to protect public health. Thus, HACCP has become an International reference system for food safety assurance.

Introduction

The risk assessment is gaining importance as the scientifically-based approach for the development of food safety and quality standards. It is a logical extension of HACCP revolution. In hazard analysis, first the hazards likely to occur in foods are identified, then an assessment is made of the severity of each hazard, and an evaluation is done of its likelihood to occur. Severity and likelihood are the two factors involved in risk assessment. Second, the increase in international trade has raised new safety and quality challenges. New approaches address the risk of cross-border transmission of infectious and hazardous agents with emerging food-borne diseases and quality problems. This has led to the development of a new safety and quality regulatory framework in 1995, the Sanitary and Phytosanitary (SPS) and the Technical Barriers to Trade (TBT) Agreements of the World Trade Organization (WTO). In these two Agreements, two provisions are of importance to fish safety and quality:

• National SPS and quality requirements should reflect standards agreed on in the international standards setting bodies i.e. Codex Alimentarius for food quality and safety.

• Domestic standards can be developed based on scientific risk assessment.

Risk assessment of microbiological hazards is identified as a priority area by the Codex Alimentarius Commission (CAC). In 1999, the Codex Committee on Food Hygiene (CCFH) in the 32nd session, identified a list of 21 pathogen commodity combinations that require expert risk assessment advice. FAO and WHO jointly launched a programme with the objective to provide an expert advice on risk assessment of microbiological hazards in foods to their member countries and to the CAC. Under which, expert groups are established to examine four priority pathogens: product pairings, e.g. Listeria monocytogenes in ready-to-eat food; Salmonella in eggs and broiler chickens; Campylobacter spp. in broiler chickens; and Vibrio spp. in seafoods. Risk assessment is therefore important throughout all aspects of the seafood industry - for companies, national governments and for international regulators.

Introduction

In all countries, food is governed by a complexity of laws and regulations, which set out the Government requirements to be met by food chain operators to ensure food safety and quality. Food laws and regulations also govern standards that ensure the safety, quality, composition and suitability of food for consumers. Food laws and regulations of any nation depends on whether a nation adopts International norms developed by the Codex Alimentarius Commission (CAC) of the Food and Agriculture Organization (FAO) of the United Nations as well as the World Health Organization (WHO).

8.1. Food Laws

Food law means legislation that regulates the production, trade and handling of food. It covers the regulation of food control, food safety, quality and relevant aspects of food trade across the entire food chain, from the production to the consumer. Food laws protect the consumers against unsafe, adulterated and misbranded food and facilitate the movement of food across borders to sustain a fair trade.

Each nation administers its own laws, regulations and standards. It is also not static always and is constantly revised and updated in all nations. The food business operators (FBO) must obtain up-to-date information on any changes made in legislation, that are likely to affect the product standards. The regulations of all nations shall be obtained from their respective websites of the national ministries.

8.1.1. International Legislations

8.1.1.1. United States of America (USA)

In USA, the Food and Drug Act (1906) and the Federal Meat Inspection Act (1906) are the first federal food laws passed to protect American consumers. Later, Food, Drug and Cosmetic Act (1938) regulated the meat and poultry products. At present, Food Safety Modernization Act (FSMA), 2011 regulates all food products. https://www.fda.gov/food/guidance- regulation- food- and dietary- supplements/ food- safety- modernization- act- fsma. Manufacturers play important role in preventing food borne illness. The Act gave the Food and Drug Administration (FDA) the authority to oversee and enforce supply chains. The Act shifts the focus towards prevention of food borne illness and insists every FBO to register with the FDA.

Introduction

Export of quality seafood products is important to have a success in international marketing. Exporters must be quality conscious and the Governments must insist on quality control and inspection. The seafood export industry in India is over 50 years old. Seafood contributes 10% of the total exports and nearly 20% of all agricultural exports. In the year 2022-23, India exported 17,35,286 MT seafood to more than 100 countries worth US $8.09 billion equivalent to Rs. 63,969.14 crore. There are over 150 fish processing facilities approved by the European Union out of the existing 350 processing facilities. The Export Inspection Council and the Marine Products Export Development Authority are working very closely with the fish processing industries for the growth of seafood exports.

The Government of India enacted the Export (Quality Control and Inspection) Act, 1963 for the development of export trade through quality control and inspection. It empowers the Government to notify the products intended for compulsory quality control and inspection prior to their export. It specifies the type of quality control required for the notified products. It recognizes standard specifications for a notified product. It prohibits the export of notified products that are not complying with export conditions. It creates a machinery for quality control and take measures to protect markets for Indian commodities. As the first step, Export Inspection Council (the Council) was established on 1st January 1964 for implementation of various provisions of the Export (Quality Control & Inspection) Act, 1963.

Introduction

The international fish trade increases day by day reaching to a tune of USD 151 billion in 2020 (FAO, 2022). Many developing countries like India gain benefits from this trade as income through net foreign exchange reached to a level of 8.09 billion USD in 2019-20. Seafood supplied by developing countries contribute to 77% of fish consumption worldwide. The European Union (EU) is the single largest market for fish and fishery products to a tune of 91.74 billion USD in 2022 as a consequence of an increased per capita consumption among its Member States. Spain, Italy, Germany and the United Kingdom are the largest importer of fish and fishery products.

To protect consumer health and to protect the territory from the introduction of animal and plant diseases, the European Community (EC) has laid down joint conditions for imports of foodstuffs. The Directorate General for Health and Consumer Protection (DG SANCO) is responsible for food safety in the EU. The import rules for fishery products are framed of high standards with respect to hygiene, consumer safety and animal health status. It is important that importing countries and food business operators (FBOs) must understand the fundamental principles and requirements of the European Food Law to ensure efficient and smooth imports. The EU system relies on Government to Government assurances without any intervention of any private type certification or standards. The Competent Authority (CA) in the country of origin is responsible for giving the official guarantees to the EU regarding compliance and conformity to all requirements of its legislation. The Export Inspection Agency (EIA) is the Competent Authority in India for issuing the required official guarantees for export of fish and fishery products. The EIA maintains a complete list of all establishments under its control.

Introduction

Nutrition is the study of how food and nutrients affect the body’s health and well-being. It encompasses all aspects of food, from the food production, processing, consumption and digestion by the body. A balanced diet included all the essential nutrients such as carbohydrates, protein, fat, vitamins and minerals for maintaining good health. The recommended daily intake of nutrients varies depending on the age, gender and physical activity of a person. The nutritional need also varies depending on the lifestyle and medical condition of a person. The nutrition facts are based on recommended daily intakes for various nutrients, which vary based on factors such as age, sex, and physical activity. These facts are given on food packaging or label, providing important information on the serving size, calories, macronutrients and micronutrients, and other ingredients.

Nutrition labels are mainly intended to guide the consumer in food selection. Nutrition information provided on labels must be true and should not mislead consumers. Nutrition labelling regulations are provided by countries to help manufacturers. The Codex guidelines on Nutrition Labelling provide guidance to member countries to develop or update their national regulations and to encourage harmonization of national standards with international standards. According to it, no food should be described or presented in false, misleading or deceptive way. Nutrition labelling cannot solve nutrition problems, instead it is one of the elements of nutrition policy.

11.1. Nutrition Facts

Nutrition Facts means the nutritional information required for most of the packaged food in many countries giving the energy value and nutrients contained in the food. Nutrition facts labels are required by regulation similar to other types of food labels. It provides detailed information on the nutrient content of the food such as the amount of fat, sugar, sodium and dietary fiber.

Introduction

Seafood provides about 25% of the global intake of animal protein and fetches a huge economy for developing nations. Many challenges concerning food safety and quality exist due to globalization and liberalization of the global f ish trade. International food safety regulatory bodies such as WTO and CAC through SPS and TBT Agreements work on ensuring food safety and quality. Adoption of risk-based analysis and implementation of the HACCP system are encouraged to maintain high seafood safety standards. International regulatory bodies set maximum residual limits for various environmental pollutants and contaminants to ensure consumer safety. Consumer education programs play important role to enhance awareness and improve transparency in the seafood supply chain. Internationally traded seafood products therefore need to meet the standards prescribed for food safety and quality requirements. In case of non-conformance, they could be detained, rejected and destroyed.

The global demand on seafood quality and safety requirement and the complexities of seafood supply chain make difficulty to ensure authenticity and traceability of seaood products in the market. Most seafood is exported from the country where it is caught while part of it via. a third country. Seafood pass-through complex supply chains involving, capture/culture, transshipment, processing, packaging, wholesale, retailing, and consumer. The global trade of seafood has led to a significant concern associated with seafood fraud.

12.1. Seafood Fraud

Seafood fraud is the practice of providing misleading information to the consumers about their product for financial gain. There are nine types of seafood fraud, which include species substitution, fishery substitution, IUU substitution, species adulteration, chain of custody abuse, catch method fraud, undeclared product extension, modern day slavery, and animal welfare

Introduction

Wastes produced during fish processing operations can be solid or liquid. Solid wastes consist of skin, viscera, fish heads, fish bones, and scraps of f lesh. Liquid wastes are the blood water and brine from drained storage tanks, water discharges from washing and cleaning, blood and soluble substances from entrails, and detergents and other cleaning agents. The effluent from the processing of fatty fish contains very high levels of oil. Overall, the wastewater from fish processing operation contains an undefined mixture of substances, mostly organic in nature.

13.1. Physicochemical Parameters of the Wastewater

13.1.1. pH

The pH is an important parameter that reveals contamination level before biological treatment. The effluents from fish processing plants are usually close to 7 or alkaline, due to decomposition of the proteinaceous matter and emission of ammonia compounds.

13.1.2. Solids Content

Solids may be present either in dissolved or suspended form. Suspended solids are objectionable as they settle in the wastewater ducts reducing their capacity or settle in the waterbody affecting bottom - dwelling flora or sometimes float reducing the light entering from the surface or remain suspended reducing the amount of light that enters the water. The settling solids are measured using an Imhoff cone. If the wastewaters contain solids that settle after 10 min, their discharge is usually not permitted. The suspended solids are measured by passing a sample through a fiberglass filter; and determining the quantity by gravimetry, after evaporation of a known volume of the filtrate.

Introduction

The term analytics and data analytics are used inter-changeably. When referring to analytics, it means “analysis of data” or “what can be learnt from an analysis of data”. In an industry like fishing industry, the researchers have been slow to adopt the tools used to portray accurate representations of data. For example, a dashboard with historical data from the past ten or fifteen years displayed on a digital map can enable the researchers to decide the places where fishing can be good. This map can help in locating the points fished during specific seasons. This will enable the researchers to filter the data on various parameters like area, year, season etc. or on any other specific parameter which can give valuable information. Similarly, this type of dashboard can affect the decision making process while fishing, like one can find the monetary value associated with each trip during a specific season or compare the values associated with two different trips to gauge the cost-benefits.

Data Analytics helps in taking most informed decisions in the fishing industry if one of the goals is to increase income while ensuring sustainability. It helps in deciding whether to reduce overhead costs or to increase expenditure to avoid overhead costs in future.

Fisheries sector undergoes continuous changes with introduction of newer technologies evolved through research and development institutions. Statistics per se deals with generation of data, data management, data analysis and information generation from data. There are varied disciplines of fisheries viz., Aquaculture, Fisheries Resource Management, Fish Genetics, Fish Biotechnology, Aquatic Health, Nutrition, Environment, Fish Physiology, and Post-harvest Technology, wherein research on practical aspects is undertaken which affect production and sustainability.

Introduction

Indian fisheries and aquaculture is an important sector of food production providing nutritional security, besides livelihood support and gainful employment to more than 14 million people, and contributing to agricultural exports. With diverse resources ranging from deep seas to lakes in the mountains and more than 10% of the global biodiversity in terms of fish and shellfish species, the country has shown continuous and sustained increments in fish production since independence. The sector constitutes about 6.3 percent of the global fish production and contributes to 0.91 percent of the GDP and 5.23 percent of the agricultural GDP. The total fish production of 13.34 million metric tonnes presently has nearly 74 percent contribution from the inland sector and rest by the marine sector. Paradigm shifts in terms of increasing contributions from inland sector and further from aquaculture have been significant over the years. With high growth rates, the different facets, viz., marine fisheries, coastal aquaculture, inland fisheries, freshwater aquaculture, and coldwater fisheries are contributing to the food basket, health, economy, exports, employment and tourism of the country. More than 50 different types of fish and shellfish products are being exported to 75 countries around the world. Fish and fishery products have presently emerged as the largest group in agricultural exports from India, with 13.77 lakh tonnes in terms of quantity and ` 45,106.89 crore in value. This accounts for around 10% of the total exports and nearly 20% of the agricultural exports, and contribute to about 0.91% of the GDP and 5.23% to the Agricultural GDP of the country.

The Pradhan Mantri Matsya Sampada Yojana (PMMSY) is an initiative launched by the Government of India to establish a comprehensive framework and reduce infrastructural gaps in the fisheries sector. The scheme was announced by the Finance Minister, Smt. Nirmala Sitharaman during her speech in the Parliament of India while presenting the Union budget for 2019–20 on 5 July 2019. The government intends to place India in the first place in Fish production and processing by implementing Blue Revolution. This scheme is in line with government’s aim to double the farmers’ income by 2022–23.The policy envisages integrating all the fishermen with agricultural farmers and providing all the facilities available through various farmer welfare schemes to the fishermen. A new dedicated Department of Fisheries was constituted in a newly carved out Ministry of Fisheries, Animal Husbandry and Dairying to implement this and other policy initiatives of the government.

Need of Analytics in Fisheries Management

New technologies are introduced for industrial vessels every day: Fuel and gear sensors, cameras, electronic catch reports etc. There is a global push to track small-scale fishing vessel. In the coming years, fisheries monitoring centers will have to adjust from tracking a few hundred vessels to tens of thousands of vessels, meaning huge quantity of data. To make sense of all this information, it must be properly analysed. The future of fisheries depends on big-data analytics

This may help in many ways. Fishing trips could be tailored to meet quotas in the shortest time reducing fuel consumption and crew costs. Real-time catch data could help administrations close a fishing zone once quota is reached. Fisheries administrations can monitor catch efforts over an entire region and decide which zones to close, improving management of stocks and fishing licenses. Fighting the challenge of Illegal and Unreported fishing contributing to over-exploitation of fish stocks. Use of disruptive technologies in fisheries and aquaculture like block chains, sensors and automatic identification systems (AIS) has the potential to change the processes profitability and sustainability of the sector

Globally used popular Data Science Software

• MS-EXCEL

• SPSS (IBM)

• STATA • MINITAB

• SAS

• R

• PYTHON

Experimental Designs

Experimental Designs are used widely to compare more than 2 groups, commonly called as treatments. It is very common in agriculture to conduct several experiments, mostly in fields to test various varieties, different levels of inputs, etc. When one is interested in crop modelling, it is necessary to identify the values of several constants, such as input efficiency, growth periods, growth rates, etc. Instead of guessing these values, it would be more appropriate to conduct experiments to derive these values empirically, which can improve the modelling efforts. The principles of experimentation were given by Sir R.A. Fisher during 1920’s, which are still relevant and found in every scientific research namely, (i) Randomization, (ii) Replication and (iii) Local Control. The following sections introduce some of the commonly used terms in Experimental Designs:

Factor: Variables which are set/considered by the experimenters in any experiment. Examples of factors are: Nitrogen, Varieties etc. Level: The various values of a particular factor considered in the experiment. Examples of levels are: Rates of nitrogen applied, different varieties considered in the experiments.

Treatment: The levels of one or more variables (Factors) set/considered by the experimenters.

Note that in many experiments, the number of variables (i.e. factors) considered may be one only.

Introduction

Importance of basic statistics in everyday life cannot be stressed enough. Inclusion of basic statistics in high school curriculum is uncommon but proves highly beneficial to supplement certain careers in future. This field may be the most widely used of all and most people don’t even know they are using it. Many of today’s brightest business minds use this study to create charts and graph that allow them to stress a certain aspect of the business they are dealing with. Market research agencies, News rooms, marketing divisions of large corporations, NGOs, accounting firms etc. are full of people who specialize in basic statistics.

Statistics is concerned with the describing, interpreting and analyzing data. It is, therefore, an essential element in any improvement process. Statistics is often categorized into descriptive and inferential statistics. It uses analytical methods which provide the math to model and predict variation. It uses graphical methods to help making numbers visible for communication purposes.

Descriptive Statistics

• Descriptive statistics summarizes or describes characteristics of a data set.

• They help to make sense of large numbers of individual responses, to communicate the essence of those responses to others

• Helps exploring and making conclusions about the data in order to make rational decisions.

• Includes calculating things such as the average of the data, its spread and the shape it produces.

• Are displayed as tables, charts, percentages, frequency, distributions and reported as measures of central tendency

• Determine if the sample is normally distributed (bell curve) as most statistical tests require the sample to have normal distribution

• Determine if the sample can be compared to the larger population

Difference between Descriptive and Inferential Statistics

Nowadays, statistics is playing a major role in the field of research; that helps in the collection, analysis and presentation of data in a measurable form. It is quite hard to identify, whether the research relies on descriptive statistics or inferential statistics, as people usually, lacks knowledge about these two branches of statistics. As the name suggests, descriptive statistics is one which describes the population. On the other end, Inferential statistics is used to make the generalisation about the population based on the samples.

There has been a surge of data in every field of research due to advancements in information technology. Data collection and storage has become much easier and cheaper in recent years. This voluminous data needs to be systematically stored for quick retrieval, process and to find useful patterns. Data mining techniques help in deriving useful patterns from data. These techniques which are also called as machine learning techniques majorly categorized as classification, clustering and association rule mining methods. Classification is a supervised learning method which needs labeled dataset for model building and prediction purposes. Clustering and association rule mining methods do not require labeled dataset and hence they are referred as unsupervised learning methods.

Clustering aims at grouping the objects based on a set of measured variables where similar objects are assigned to one group. For example, let us say, if we have collected information on 50 fish pond parameters (50 variables) and we wish to find the groups in terms of pond management (like well managed to poorly managed), with cluster analysis, we can group the ponds based on pond variables. In the process of clustering, each pond is assigned to one of the groups made. The question is how many natural clusters present in the data as in many cases we would not be getting perfect clusters of disjoint sets. We can achieve better accuracies in cluster formation only by trial and error. Good clustering criteria are to see that there is minimum with-in cluster variations and maximum between cluster variations.

Cluster analysis has several applications in fisheries research. It could be used to group fish stocks from different regions, categorise ponds based on their technical efficiencies, identify the farm clusters with high disease risk, group farmers based on their preferences, agro zoning based on climatic variables and culture practices. Cluster analysis is also applied in fish bioinformatics to group the similar sequences.

Product Development and Marketing

Several efforts are being made on the research front for development of novel products from fish which have enhanced shelf life, retain the freshness and nutrients and are safe to consume. During the course of product development, which are in many stages, studies are conducted prior to commercialisation to ensure the acceptance of a product.

In a business, understanding consumer behaviour plays an important role in success. To be in a business for a long time, it is essential to know what the consumer prefers and why. Consumers make the buying decisions based on a number of factors. The purpose behind studying the buying behaviour and consumer preference is to produce and market products which may better meet the needs of a consumer. The emerging fastfood culture among the young and affordable has brought focus on processed food and its demand in the domestic food market in India. Domestically, spending on food and food products constitutes the largest portion of the Indian consumer’s spending – more than a 31% share of wallet. Evaluation of consumer preferences before introducing a new product will help the marketer to refine the product for better reach.

Conjoint Analysis

Conjoint analysis is a popular technique used in marketing research to study the features a product that should possess to have a wide consumer reach. Conjoint analysis was initially conceptualised by Luce and Tukey (1964) and further developed by Green and Rao (1971) for marketing research. It employs a decompositional method to estimate the structure of consumer preferences and consumer utility values of different attributes of a product or service. It is a decompositional method that disaggregates the structure of consumer preferences into utility values. The relative importance of a product can also be estimated using this method.

Introduction

This chapter is intended to throw light on some statistical and econometric methods used for analysing time series data with specific emphasis on basic concepts related to time series analysis, co-integration techniques as well as forecasting techniques such as ARIMA model. Time series analysis is often helpful in revealing the broad patterns associated with longitudinal data, which in turn would aid in important economic and policy decisions. In fisheries sector too, economic variables such as market demand and supply, prices, etc. are of prime importance and often come in longitudinal format. There are a number of alternative methodologies available in the time series literature to determine relevant parameters pertaining to longitudinal data and the ensuing sections are set apart to delve deeper into this realm.

Some Key Concepts

Stationary Stochastic Process

A random or stochastic process is a collection of random variables ordered in time. A stochastic process is said to be stationary if its mean and variance are constant over time and the value of covariance between two time periods depend only on the distance or the gap between the two time periods and not the actual time at which the covariance is computed. In the time series literature, such a stochastic process is known as a weekly stationary or second order stationarity or covariance stationarity.

Introduction

Resources must be managed effectively to achieve maximum sustainable agricultural production from limited natural resources. Many of the resources that agriculture depends on (such as water and land) are finite and need to be well managed for long term sustainability. In most cases, this means avoiding adverse effects on the society and environment. With the development of agricultural sectors, the utilization patterns of natural resources in agriculture are important concern for policy makers in present climate change scenario. Unlike other production activities, agricultural activities also utilize factor resources to produce several marketable products or services. The way the natural resources are utilized in agriculture and its concern for society and environment, plays a vital role in economic viability and ecological sustainability of agriculture.

There are several conventional methodologies to estimate the level of profit and efficiency of production system at enterprise level. Only marketable factors are considered in conventional methods keeping the non-marketable component of production system away. Non-marketable component of a production system includes various social and environmental dimensions of it. Nammalwar (1997) has explained the concept of environmentally sound and sustainable enterprises, which include the physical resources, ecological resources, human use value, quality of life values with either way impact of agriculture and environment. In recent years, non-marketable dimensions of agricultural activities have been given importance because of its concern for the environment and society. This chapter provides a methodology that incorporates non-marketable component of agricultural enterprise besides its marketable component. The Resource Cost Ratio (RCR) approach is a modified methodology developed by Debnath et al. (2010) from Domestic Resource Cost Ratio (DRCR) that Morris (1990) has applied at macro-economic level to determine the comparative advantage between countries.

Introduction

The term ‘Fish Marketing’ is composed of two broad meaning term ‘Fish’ and ‘Marketing’. Before discussing the methodological issues of fish marketing data analysis, we must understand the broader meaning of it as both words are being used frequently with a précised meaning. Google dictionary explains fish as ‘A limbless cold-blooded vertebrate animal with gills and fins living wholly in water’. But ‘fish’ as a component of fish marketing or social science study, means a product and a variety of product, which has different time, space and form utilities for consumers.

The word ‘marketing’ is not merely buying and selling of fish, rather it connotes a series of activities involved in moving goods or services from point of production to the point of consumption. So ‘fish marketing’ is defined as physical and institutional set up to perform all activities involved in the flow of fish, fish products and services from the point of initial fish production until they are in the hands of ultimate customers.

It includes assembling, handling, storage, transport, processing, wholesaling, retailing and export of fish and fishery products as well as accompanying supporting services such as market information, establishment of grades and standards, community trade, financing and price risk management and the institutions involved in performing the above functions.

It is desired to have an efficient and well planned distribution networkso that fish and fishery products move from the place of landing or production to the place of consumption at cheapest cost with quality –intact, ensuring the maximum price realization to the farmers or fish producers. It is really challenging to the public agencies involved to meet the requirements of all three major players, viz., fishermen or fish farmers, consumers and traders.

It includes all activities involved in creation of time, place, form and possession utility. Philip Kotler explained marketing as the science and art of exploring, creating, and delivering value to satisfy the needs of a target market at a profit. ‘Fish marketing’ is different from marketing of other goods and services and even differs a bit from marketing of variousagricultural goods and services.

Setting

The basic difference which dovetails most of the animal breeding experiments is the unbalancedness of the data collated with respect to factorial classes thereby making non-orthogonal nature of the effects involved ubiquitous. Henderson, C.R. (1953), through a series of seminal works dealt with these types of data and came out with three distinct methods to estimate the variance components emanating out of such non-orthogonal animal experiment data. Before discussing those methods, let us delve a bit on the challenges in estimating the variance components in animal breeding data. There are two major reasons, first, several methods of estimation are available (most of which are reduced to the analysis of variance method for balanced data), but not one of them has yet been clearly established as superior to the others. Second, all the methods involve relatively cumbersome algebra; discussion of unbalanced data can therefore easily deteriorate into a welter of symbols, a situation which functions as the anti-appetizer to applied researchers.

A safe starting point towards understanding the nuances of dealing with unbalanced data could be the paper by Henderson (1953) which is quite seminal in nature. The methods described have been often referred to as the gold standard in the area of estimating variance components from unbalanced data for many years to come. Of the three, method 1 is simply an analogue of the analysis of variance method used with balanced data and method 2 is used to correct a deficiency of method 1 that arises out of mixed models and the last one is quite different and involves the method of fitting constants so often used in fixed effects models. Let us see these methods in a bit more detail in the ensuing passages.

Introduction

Regression analysis is one of the most widely used techniques for studying relationships involving multiple variables for analysing data by expressing a relationship between a variable of interest (the response) and a set of related predictor variables. The regression models include linear and non linear approaches assuming appropriate functional forms. A good account on regression analysis and related topics can be found in Draper and Smith (1998), Montgomery et al. (2001), Chatterjee and Hadi (2006) etc. In this write-up, regression model fitting, some of the detection techniques which are useful in detecting the problem of multicollinearity between the so-called ‘independent variables’ and also outlier detection in data are discussed. Linear regression with qualitative regressor variables is also discussed. Moreover, variable selection procedures, goodness of fit measures for model adequacy and validation are also discussed. In addition, non-linear regressions viz., logistic (both binary and multinomial) when the response variable is qualitative are also covered.

Multiple Linear Regression Modeling

Let the response variable (variable to be forecasted) be denoted by Y and the set of predictor variables, by X1 , X2 , …, Xp , where p denotes the number of predictor variables. The true relationship between Y and (X1 , X2 ,…,Xp ) can be approximated by a multiple linear regression model given by

Introduction

A fundamental issue when analysing trade policy reform in global seafood market is the extent to which domestic agricultural commodity markets in developing countries respond to changes in international prices. Price trans mission from the world to domestic markets is central in understanding the extent of the integration of economic agents into the market process.

Studies on the transmission of price signals are founded on concepts related to competitive pricing behavior. In spatial terms, the classical paradigm of the Law of One Price, as well as the predictions on market integration provided by the standard spatial price determination models (Enke, 1951; Samuelson, 1952; Takayama and Judge, 1972) postulate that price transmission is complete with equilibrium prices of a commodity sold on competitive foreign and domestic markets differing only by transfer costs, when converted to a common currency. These models predict that changes in supply and demand conditions in one market will affect trade and therefore prices in other markets as equilibrium is restored through spatial arbitrage.

The absence of market integration, or of complete pass-through of price changes from one market to another has important implications for economic welfare. Incomplete price transmission arising either due to trade and other policies, or due to transaction costs such as poor transport and communication infrastructure, results in a reduction in the price information available to economic agents and consequently may lead to decisions that contribute to inefficient outcomes. Fisheries and seafood food trade policy reform, especially, is a priority issue in the next WTO negotiations, as trade liberalization is viewed as encouraging allocative efficiency and long run growth.

Introduction

Indian agriculture, including fisheries, is highly monsoon dependent and effect of climate change is immense on its large tracts of rainfed farms. The effects of climate change could be thwarted through better adaptation techniques using all information available with various agencies concerned with agriculture and using advanced analytical tools. Presently, in the country, there is a gap in the capability in capturing, processing and analyzing huge source of information generated in Indian agriculture. This task can be accomplished using Big Data Platform which works in cluster mode and provides the capability of handling huge volume of data, capturing streaming data or real time data and also can accommodate unstructured data. As per FAO, 70 percent in increase in food production in another 30 years is required to overcome the increasing global food demand. It may not be possible to achieve that target due to variety of problems such as reduction in land for cultivation, climate change, and various other factors, such as increasing the fish production etc. Improvement in crop genetics, application of fertilizer in higher dosages, irrigation facilities, etc. may not be possible in future. We need to create a big data platform involving important parameters on crop production viz., soil, soil temperature, water requirements, and relative humidity, pests and diseases, and micro and macro nutrients in temporal and spatial. Now, since available data is properly utilized for making valid analytics by the farming community due to certain issues. Even the data created is incompatible, data available from various sources is also not compatible among themselves due to which decision making is also a big challenge. Due to the incompatibility of agricultural data from different sources, farmers do not have the accessibility to vast pool of available information for making effective, efficient and timely decisions.

Big Data in Agriculture (including fisheries)

Big data, an emerging data driven system helps in precision agriculture based on data collected. This helps farmers in making efficient decisions on sowing, planting, fertilizing and various other farm operations including

harvesting crops at the appropriate time. Of late, sensors are placed in the fields to collect data on related parameters viz., soil temperature and moisture relative humidity, wind speed, weather, etc. which help in crop growth. Images obtained using satellites are helpful in monitoring the crop growth during crop period. Agro-produce includes not only yields obtained from crops but also include produce from horticulture, livestock, fisheries, and other systems also. Agriculture is dependent on various parameters such as climate, seed, soil cultivation practices, agronomic practices, irrigation requirement, fertilizers pesticides, weeds, harvesting, post harvesting techniques, etc. Data collected on all these parameters would help in estimation of yield and other relevant parameters. Governments, Universities, Research departments, Agro-business and Agri-input companies generate, maintain and use voluminous data related to various farm management practices and other related issues say insurance marketing, supply chain, packaging, distribution, etc. This voluminous and wide variety of data poses several challenges for making effective decisions. Information on various fish related parameters can be collected from the stakeholders and a big data platform can be developed for effective decision making.