eChapters

Introduction to Corporate Level Strategy

Corporate level strategy pertains to the choices and initiatives undertaken by a company's senior management to define the overarching direction and breadth of the organization. It entails making decisions regarding which industries or markets to engage in and how to distribute resources among various business units.

Scope of Decision-Making: Corporate level strategy concentrates on the entirety of the organization rather than individual business units or functional areas. It involves strategic decisions related to diversification, vertical integration, mergers and acquisitions, strategic alliances & resource allocation.

Purpose: The primary goal of corporate level strategy is to create value for shareholders by achieving a sustainable competitive advantage and maximizing the overall performance and profitability of the organization. It involves assessing the external business environment, identifying opportunities and threats, and leveraging internal capabilities to gain a competitive edge.

Diversification: One key aspect of corporate level strategy is deciding whether to pursue a strategy of diversification. Diversification can be either related (expanding into industries or markets related to the company's current business) or unrelated (entering completely new industries). The decision to diversify involves assessing the potential benefits, risks, and synergies associated with entering new markets.

Organizations Indebtedness Towards Society

The organizations in the present world operate as an open system by having ongoing interactions with the society for their existence and effective functioning. There is an interdependence between corporations and societies and as such, company’s activities have a direct impact on the communities with which they work.  As a part of such interactions, the organizations use valuable resources of the society, for producing goods and services, which are exchanged with the customers for a profit margin. Due to these exchanges, the business organizations take away the profits reflecting the debt they owe to the society and the world.

Abstract
Corporate Social Responsibility is one of emerging term now-a-days in the corporate arena. Sustainable growth is possible only when all sphere of the society is self sustained. Since the early 1990’s, corporate responsibility issues including social obligation of corporations have attained prominence in political and business debates. This is mainly in response to corporate scandals but also due to realisation that development centred only on economic growth paradigms is unsustainable and therefore there is a need for more pro-active roles by states, companies and communities in a development process aimed at balancing economic growth with environmental sustainability and social cohesion. Some people think sustainability is all about environmental issues. Others see it in terms of the bottom line. And then, of course there are the people who use the term synonymously with corporate social responsibility. CSR and Sustainable development are two different concepts having different traits. Corporate social responsibility (CSR) promotes a vision of business accountability to a wide range of stakeholders who are directly and indirectly dealing with corporate entities, besides shareholders and investors. Therefore, there is a need for evaluating the working of CSR on social sustainability. Besides, this paper try to identify the key areas of concern are environmental protection and the wellbeing of employees, the community and civil society in general, both now and in the future (by international institute for Sustainable Development),various issues and challenges faced by corporate bodies.

Seed yield is the foremost important attribute and is the end product of many complex component characters which singly or jointly influence the seed yield. Seed yield does not possess gene per se as such. It is the interaction phenotype of the harmonious understanding, mutual adjustment and manifestation of its component characters. As most of the component characters are polygenic, they are greatly influenced by the environment. So, the selection of genotypes based on yield as such is not likely to be effective. The information on the strength and direction of association of the component characters with seed yield and also among themselves will be very useful in formulating an effective breeding programme for seed yield improvement in a given time. Correlation studies provide about the magnitude and direction of genetic association between the seed yield and its component characters.

Correlation coefficients provide the measure of association between two characters. But, they do not provide the causal basis of such association. Further, correlation between seed yield and its component characters are often misleading due to the inter-relationship that exist among the component characters and the operation of size symmetry and component compensation that thwart the breeding progress. The direct contribution of each component to the seed yield and the indirect effects it has through its association with other components cannot be differentiated from mere correlation studies. This is how, it became necessary for a plant breeder to have information on the direct and indirect effects of these components on the seed yield to identify the key characters for improvement.

Correlation and regression are essential statistical tools for examining relationships among climate variables and agricultural responses. Correlation measures the strength and direction of association, while regression develops mathematical relationships for explanation and prediction. This chapter discusses their application to rainfall, temperature, humidity, evapotranspiration, crop growth and yield. It explains simple and multiple relationships, assumptions, interpretation, model fitting, predictive power and potential errors. These methods support crop-weather modelling, yield forecasting, climate-impact assessment and agricultural decision-making. By identifying how climatic variables influence biological and production processes, correlation and regression analysis help researchers generate reliable predictions and design more resilient and productive agricultural management strategies under changing environmental conditions.

10.1 Introduction

In previous lessons we have been dealing with problems connected with variation occurring in any one variable, say the income of a person, the height or weight of an individual, the wage of a worker in a factory, the sales of a shop, demand of a commodity etc.  The values of a single variable were obtained from every member of the population and the different characteristics were described by certain descriptive constants after grouping into frequency distribution.  In this lesson, we shall be dealing with problems wherein there are paired variables and every individual or member of the population exhibits two values, one for each of the variables under consideration.  Example of the two variables which are to be studies together are (i) the income and expenditure of a household, (ii) the price and demand or supply of a commodity, (iii) the height and weight of a student, and (iv) the grain yield and straw yield of paddy, (v) Height of father and height of son, etc.

Concept of correlation was given by Karl Pearson in 1890.

The study of strength and nature of relationship between two variables is called correlation. Two variables are said to be correlated, if the change in one variable affects the other variable. Correlation is also known as covariation.

Bivariate Distribution: Distribution involving two variables is known as bivariate distribution. For example, Height and weight of persons, yield and production of a crop in.

On basis of type of association between variables, correlation is of two types:

If x and y are related, we can study degree of relationship between them which is called correlation.

Y = f(x)=a+bx where y is a dependent variable and x is an independent variable. If x is known, y can be known.

X = f(y). Here x is a dependent variable and y is an independent variable or auxiliary variable.

6.1 Correlation

The term correlation indicates the relationship between two such variables in which with changes in the values of one variable, the values of the other variable also change. In short, the tendency of simultaneous variation between two variables is called correlation.

Correlation

In a statistical analysis, when two variables are studied simultaneously, then it is called “Bivariate study’. Now, in a bivariate study, if it is found that change in the values of one variable then in sympathy with the change in the values of other variable, then these two variables are said to be associated and the association is termed as correlation. In other words, the term correlation indicates the relationship between two such variables in which with changes in the values of one variable, the values of the other variable also change. In short, the tendency of simultaneous variation between two variables is called correlation.

Types of Correlation

Correlation can be classified by-

• Positive and Negative correlation: The correlation may be classified according to the direction of change in the two variables. In this regard, correlation may be either positive or negative. Positive correlation refers to the movement of variables in the same direction. Negative correlation efers to the movement of variables in the opposite direction.

• Simple, Partial and Multiple correlations: When only two variables are studied it is a problem of simple correlation. When three or more variables are studied simultaneously, it is a problem of multiple correlations. On the other hand, in partial correlation we recognize more than two variables, but consider only two variables to be influencing each other the effect of other influencing variables being kept constant.

• Linear and non-linear correlations: In linear correlation for every unit change in the values of one variable, there is constant change in the value of other variable. The perfect positive and negative correlations are also linear correlations. In non-linear correlation the change in the values of one variable does not have a constant ratio to the change in the other variable.

Correlation coefficient

We measure the degree of association between two variables by calculating Pearson’s product moment correlation coefficient, usually just called the correlation coefficient.

It was developed by Karl Pearson from a related idea introduced by Francis Galton in the 1880s, and for which the mathematical formula was derived and published by Auguste Bravais in 1844. In 1896, Karl Pearson published his first rigorous treatment of correlation and regression in the Philosophical Transactions of the Royal Society of London.

The linear correlation coefficient (sometimes called Pearson's Correlation Coefficient), commonly denoted, is a measure of the strength of the linear relationship between two variables.

• We say that we have perfect correlation if all the points lie on the line; in this case, the value of the correlation coefficient takes one of its extreme values, either +1 or −1 (Figure 7a and 7b).

• We have positive correlation if the sign of the correlation coefficient is positive; then there is a direct relationship between the two variables so that as one variable increases in value, the other variable increases (Figure 7a) or there is a tendency for it to do so.

• We have negative correlation if the sign of the correlation coefficient is negative; then there is an inverse relationship between the two variables so that as one variable increases in value, the other variable decreases (Figure 7b) or there is a tendency for it to do so.

• We have no linear association (i.e. the variables are uncorrelated) if the correlation coefficient is zero; then there is a random scatter of points with no indication of a linear relation between the variables (Figure 7c.). Note that a non-linear relationship between the variables can also give a correlation coefficient of zero.

Germination between M₁ and M₂ had a non-significant relationship in germination between M₁ and its corresponding M₁ progenies in M₂ (Table 27). Probably the reduction in the germination in M₁ might be very highly and significantly influenced by the conditions prevailing in germination and physiological disturbances that would be strictly associated in M₁ alone. Whereas the survival of the seedlings between M₁ and M₂ showed a strong positive relationship. The differential behaviour of the mutagens affecting germination and survival was also evident as discussed elsewhere.

However, seedling height on 10^th day sorted a differential relationship between M₁ and M₂. It was negative and non-significant. A non-significant relationship was exhibited for seedling height on 30^th day between M₁ and M₂ in all the doses. It may be interpreted that extent of physiological disturbances that occurred in the early stages and the extend of recovery mechanism that operated subsequently may be the major cause for this; not withstanding the haplontic and diplontic selection that operated in the biological system. Further the type of physiological disturbances happened, whether the enzyme systems affected or a substantial amount of toxic substances produced besides the genetical causes have not been studied in the present investigation. Moreover if the reduced growth was due to mitotic arrest in the meristamatic regions of the roots of M₁ plants, the disorder may not be completely inherited to its offspring’s (M₂ plants), in that sense selection at the cell level damages might occur in the M₁ itself and the selection for a cell with normal mitosis and extent of chromosomal damages that will be tolerated alone might be selected and hence the effect in M₁ need not be always related with M₂; it also depends upon the potency of the cell to recover from the mutagen induced damages. The ability of the cell in general, should be more in M₁ than in M₂ recover the disorder after several cell generations.

This chapter begins with an introductory overview, providing a basic understanding of correlation and its types. It guides readers through in-depth analysis using R, demonstrating how to apply these concepts practically.

Correlation

Correlation analysis is a statistical method used to evaluate the strength and direction of the relationship between two variables. This analysis is vital in identifying and understanding how variables are interconnected within a dataset, providing insights into their mutual influences.

Key aspects of correlation include

• Range of the correlation coefficientThe value of the correlation coefficient (“r”) falls within the range of −1 to +1.

• Independence from origin and scaleThe correlation coefficient (“r”) remains consistent regardless of any changes in the origin or scale of the variables.

• Unit independenceThe correlation coefficient is independent of the units of measurement

of the variables.

• Relationship with independenceWhile uncorrelated variables are generally independent, the reverse is not necessarily true; independent variables will always be uncorrelated.

6.1 Learning Objectives
After going through this chapter, you will be able to:
i) Understand the meaning, significance, and properties of correlation;
ii) Know the various types of correlation;
iii) Comprehend the computation process of various types of correlation;
iv) Appreciate the limitations of correlation.

6.2 Introduction

Correlation is a fundamental statistical concept that measures the degree of association or relationship between two or more variables. Correlation helps us to understand how changes in one variable correspond to changes in another. Correlation values range from -1 to 1; where -1 indicates a perfect negative correlation, +1 represents a perfect positive correlation and 0 suggests no linear correlation between the variables. The sign and magnitude of the correlation coefficient provide information about the strength and direction of the relationship between the variables. Correlation analysis is a multipurpose tool with various applications, such as identifying the strength of relationships between stock prices and market indices, assessing the impact of education on income levels, or determining the association between weather conditions and crop yields. Understanding correlation is essential for making informed decisions, drawing conclusions from data, and developing predictive models in numerous fields of study and practice.

In genetic studies it is necessary to distinguish two causes of correlation; is chiefly pleiotropy, though linkage is a cause of transient correlation, particularly in populations derived from crosses between divergent strains. Pleiotropy is simply the property of a gene whereby it affects two or more characters, so that if the gene is segregating it causes simultaneous variation in the characters as affects. For example, genes that increase growth rate increase both stature and weight, so that they tend to cause correlation between these two characters. The degree of correlation arising from pleiotropy expresses the extent to which two characters are influenced by the same genes. But the correlation resulting from pleiotropy is the overall, or net, effect of all the segregating genes that affect both characters. Some genes may increase both characters, while others increase one and reduce the other the former tend to cause a positive correlation the latter a negative one. So pleiotropy does not necessarily cause a detectable correlation. The correlation resulting from environmental causes is the overall effect of all the environmental factors that vary; some may tend to cause a positive correlation, others a negative one.

Introduction

Nucleotide and protein sequences construct the core of Bioiformatics. These biological sequences form complex and very large datasets. Various Statistical techniques have been used for analysis and extraction of precise information form small as well as large biological datasets. Evolution and natural selection makes biological sequences redundant and statistically biased. Once the mechanisms involved in such biases have been characterized, their analysis and systematic investigation become valuable tools for use in predicting the properties of other biological sequences. This biased nature results in relative codon usage value among the synonymous codons or Relative Synonymous Codon Usage (RSCU) value. Codon usage variation within a single genome can be an important source of information about gene expression levels and events of horizontal gene transfer (Medigue et al., 1991). The analysis of codon usage patterns can be traced back to when first molecular sequence databases were being colleted (Grantham et al., 1981). In order to evaluate the codon and amino acid usage variation, multivariate analysis options like Correspondence Analysis, Principal Component Analysis, Cluster Analysis, Factor Analysis, Multidimensional Scaling and Eigenanalysis Ordination are available (Morrison et al., 1994). It is well established that codon usage by its nature is multivariate. These methods provide a low dimensional point representation of genes, where the proximity of gene specific points indicates (CoA) a similar codon usage of associated genes. Correspondence Analysis is an exploratory graphical approach that requires contingency tables and generates results in the form of tables, scattered plots and graphs. CoA can identify the major sources of variation in the dataset. The output from a CoA can be used to evaluate other aspects of genes, such as base composition, expressivity, aromaticity and location on the genome (Thiouse et al. 1997).

Corynebacterium diptheriae was first observed by Klebs in 1883 and described in details by Loeffler in 1884. So it is also known as ‘Klebs-Loeffler bacillus’. In 1888, Nocard isolated a similar type of bacteria from cases of bovine farcy. In 1894, Preisz described it completely and revealed its similarities with the diphtheria bacilli. Latter it was named as Corynebacterium pseudotuberculosis (Preisz-Nocard bacillus). Bollinger (1890) first reported C. renale from the cases of pyelonephritis in cows. Magnusson (1923) first described C. equi (Rhodococcus equi) form suppurative pneumonia of a foal.

Properties of genus

1.   Morphology

Corynebacterium are gram positive, pleomorphic bacteria ranging from coccoid to filamentous rods. The size varies from 0.5-0.6 µm by 1.0- 3.0 µm. Some of the species appear as packets of parallel cells (palisade arrangement) or show ‘V’ shaped form (Chinese letter arrangement) in the microscopic field (Fig.1and Fig.2). The cell wall peptidoglycan contains meso-diaminopimelic acid (meso-DAP). The arabinose and galactose are major cell wall sugars. Short-chain mycolic acids (corynomycolic acids, 22–36 carbon atoms) are present. This kind of cell wall structure is impermeable to the hydrophilic compounds. However, the ‘porin’ present in the cell wall sometimes helps in import of the hydrophilic substances. Mycolic acid containing cell wall helps in intracellular survival within the macrophages. Corynebacterium is non acid fast, non-sporulating, non-capsulated and non-motile bacteria (except C. aquaticum)
.

Cosmos is a flowering plant belongs to family Asteraceae. Cosmos bipinnatus is ornamentally important species grown for garden display. The word cosmos is derived from the Greek word “kosmos”, which means a balanced universe or order, harmony and often referred to as Mexican Aster. The species name is from the Latin “bipinnatus” meaning “twice-pinnate” The botanical epithet is from the Latin “pinnatus” meaning “with leaflets arranged in opposite pairs”. Cosmos flowers are produced in a capitulum. Modern varieties come with single or double flowers, picotee edges, and even furled petals in the variety Seashells. Ornamental uses of cosmos include cut flowers and as border annual in the gardens. It is a very popular flower for summer bedding. Cosmos has a pleasant aroma and attracts butterflies to the garden. Essential oil extracted from leaves of cosmos. The major constituent of C. bipinnatus contained 15-17% beta-elemene, 15-17% beta-caryophyllene, 10-21% germacrene D and 12-15% bicyclogermacrene (Menut et al., 2000).

Cosmos is a flowering plant belongs to family Asteraceae. Cosmos bipinnatus is ornamentally important species grown for garden display. The word cosmos is derived from the Greek word “kosmos”, which means a balanced universe or order, harmony and often referred to as Mexican Aster. The species name is from the Latin “bipinnatus” meaning “twice-pinnate” The botanical epithet is from the Latin “pinnatus” meaning “with leaflets arranged in opposite pairs”. Cosmos flowers are produced in a capitulum. Modern varieties come with single or double flowers, picotee edges, and even furled petals in the variety Seashells. Ornamental uses of cosmos include cut flowers and as border annual in the gardens. It is a very popular flower for summer bedding. Cosmos has a pleasant aroma and attracts butterflies to the garden. Essential oil extracted from leaves of cosmos. The major constituent of C. bipinnatus contained 15-17% beta-elemene, 15-17% beta-caryophyllene, 10-21% germacrene D and 12-15% bicyclogermacrene (Menut et al., 2000).

ORIGIN AND DISTRIBUTION

Cosmos is native to scrub and meadowland in Mexico where most of the species occur, Florida and the southern United States, Arizona, Central America, and to South America in the north to Paraguay in the south.

It can also be found in natural areas in much of North America, where it is a garden escape (introduced species) and in some habitats becoming a weed. Cosmos sulphureus originates from Central America (Mexico) and northern South America, where it is still found in the wild. It has been introduced as an ornamental in many countries all over the world, in tropical Africa e.g. in Senegal, Cameroon, Sudan, Tanzania, Malawi, Zambia, Zimbabwe, Mozambique, Réunion and Mauritius. Sometimes it has escaped from cultivation and behaves like a weed, e.g. in Tanzania, Malawi, Zimbabwe, the United States and Canada. Cosmos caudatus is indigenous to tropical America. It was introduced by Spaniards into the Philippines, possibly because it was used by them as a vegetable at sea. Now it is pantropical, including Southeast Asia, where it is cultivated but also occurs in a naturalized state.

Abstract: Cosmos, popular as garden annual in many parts of the world, has its origin in Mexico. Cosmos is cross pollinating and progeny can segregate widely for traits due to heterozygosity. Self and cross incompatibility, self and intersterility, limited fertility, reproductive barriers and seed sterility often pose significant challenges to breeders. The breeding objectives include development of suitable indoor plants, less susceptible to powdery mildew and more tolerant to abiotic stress. The biotechnological skills can be attempted in breeding.

Keywords: Breeding, self incompatibility, sterility, hybrid seed production.

12.1 Introduction

It is important to note that growing crops in a greenhouse requires a significant f inancial and administrative commitment. In order to ensure profitability, firms need to consider both cash flow and profitability. An enterprise budget can help address profitability potential by itemizing costs incurred across a typical production cycle. On the other hand, a cash flow budget is used to analyze the cash inflows and outflows of the enterprise over a fixed period of time.

efficiency, and support strategic decision-making. When integrated with data analytics, cost analysis becomes more precise, data-driven, and adaptable, allowing firms to optimize resource allocation and enhance profitability. The process begins with the collection and classification of cost data. Costs are typically categorized into fixed, variable, and semi-variable components. Fixed costs remain constant regardless of production levels, while variable costs fluctuate with output, and semi-variable costs exhibit characteristics of both. Data analytics tools assist in organizing and cleaning large volumes of financial data from accounting systems, ensuring accuracy and consistency. Proper classification is essential, as it forms the basis for meaningful cost analysis and modeling.q

7.1 Investment Analysis for Agribusiness Projects

Financeis the Art and science of managing money. Financial Management is the manage rial activity concerned with the planning and controlling of the firm’s financial resources. Finance can be classified as Public finance, Private finance (Personal & Business), and finance for Non-Profit organizations. The objectives of financial management are Profit Maximization and Wealth Maximization.

The Cash flow is the net amount of cash and cash-equivalents moving into and out of a business.The types include Operating Cash Flows, Investing Cash Flows and Financing Cash Flows. Annuity cash flows are a series of periodic cash flows of equal amount. The time value of money is the change in the value of money as a result of change in the time duration. They are broadly classified into Future Value of Money and Present Value of Money.

Capital Budgeting is long-term planning form aking and financing proposed capital outlays. It is the process of making investment decisions in capital expenditures. The influential factors ofCapital Budgeting are Urgency, Degree of certainty, Intangible factors, Legal factors, Availability of funds, Future earnings, Obsolescence, Cost considerations, R&D projects and Competitivepressure.

Problem: Cost of cultivation depending upon the seed and time. More yields can be obtained during right time of sowing, but net profit is very less due to the glut in the market. We can get more return from early or late sown crop during both the season due to the high cost in the market.

Theory of Costs

In both short-run and long-run analyses, there exist different cost curves.

Short run is the duration of a given factor or factors. Equipment and business owners are typically fxed in the near term

Long run is the period over which all factors become variable.

Fixed costs: are those expenses that remain constant regardless of output or production levels.. Eg: depreciation, annual maintenance cost etc.

Variable cost: are those expenses that change depending on the volume of output eg : inputs/raw material costs, wages etc.

Short Run Cost Curves

There are seven cost concepts or curves in short run analysis. They are :

1. Total cost (TC)
2. Total Fixed cost (TFC)

There are different types of greenhouses, the low cost and high cost or low technology or high technology greenhouses. The cost of greenhouse and expenditure on crop production under these greenhouses would vary according to technology to be used and the crop is to be produced. The cost would vary from place to place with location of greenhouse. For each type of greenhouse its cost would vary according to geo-climate, the production practices and input expenditure/availability. The cost of construction of greenhouse in 2019 hence varies from Rupees 500 to 6000 per square meter.

Cost estimation is a critical step in the planning and implementation of conservation structures, providing a foundation for project approval, budgeting, and economic evaluation. For drop spillways—hydraulic structures used in soil and water conservation—the process involves calculating all expenses associated with materials, labor, and ancillary charges.
Drop spillways are engineered to safely transport excess runoff from higher elevations to lower ground levels, preventing erosion and structural degradation. Commonly used in agricultural watersheds, these structures play a vital role in controlling gully erosion, managing stormwater, and maintaining land productivity.
Accurate cost estimation includes:
• Quantifying construction materials such as concrete, masonry, reinforcement bars, and pipe outlets.
• Calculating labor costs based on the skilled and unskilled labor required for excavation, form, and structural assembly.
• Adding overhead charges, including land revenue, administrative costs, and potential audit expenses.
A detailed cost estimate ensures that the project remains within budget while meeting safety, durability, and environmental standards. It also aids in comparing alternatives and securing funding or approvals from governing agencies.
COMPONENTS OF A DROP SPILLWAY
Estimating the cost of different conservation structures involves analyzing both material and labor expenses specific to each type of structure. This process plays a vital role in project approval and economic assessment. It includes calculating material quantities, labor charges, and additional costs such as audit fees and land revenue.

Aim

To determine cost of operation of processing machineries with available data.

Total operation cost

For calculation of cost of operation of processing machineries, two types of cost viz., fixed cost and variable cost to be estimated.

13.1. Introduction
Knowledge regarding various relationships existing between costs and output is necessary to comprehend the concepts of equilibrium conditions of different firms under different market conditions. Basically we require data on output, fixed costs, variable costs and the prices of inputs and outputs. From this data we finally derive all the seven cost concepts, viz.,TFC, TVC, TC, AFC, AVC, AC and MC. These cost concepts would have implications for output expansion of the firms and equilibrium position of the firms in different time periods. In the cost theory, economists use different names for cost concepts under different context. They are money costs or nominal costs, real costs, opportunity costs, economic costs, implicit costs, explicit costs, deflated costs, social costs, short run costs, long run costs, separable costs, etc.
Nominal Costs or Money Costs
These are usually expressed in money terms at current prices. Nominal costs of production refer to per unit cost of production of output at current market prices.
Real Costs
When the costs of inputs and input services are expressed at constant prices they become real costs.

5.1. Cost concepts

Cost refers to the money value of effort extended or sacrifice made in producing an article or rendering a service or achieving a specific purpose.

Expenses incurred in organizing and carrying out production process.

Includes outlays of funds for inputs and services.

Total costs: Money value of all inputs used in the production process.

1. Basic Information on the Country and  Agricultural Status
 
1.1. Location of Côte d’Ivoire

Cote D’ivoire (Ivory Coast) is located in West Africa, between the Equator and the Tropic of Cancer, with an area of 3, 22,462 km². It is bordered on the north by Mali and Burkina Faso, no the west by Liberia and Guinea, on the east by Ghana and on the south by the Gulf of Guinea, stretching across nearly 550 km. The economic capital Abidjan is with a population of more than 3 million people and Yamoussoukro, the political capital, has more than 1,50,000 inhabitants.

1.2. Population 
The Ivorian population is 1,53,66,672 people in 1998, of which 26 per cent are foreigners (4,000,047), with an annual population growth rate of 3.3 per cent and a density of 48 habitants/km². 53.8 per cent of the population is under the age of 20 years. The age group between 21 and 60 years is 41 per cent. These figures show the youthfulness of the Ivorian population. The average life expectancy is 65 years.

Cotton is often called as “white gold”. True to its name cotton supports the largest agro based industries in India and cotton industry ranks first in the agro based industries and engages 4 to 5 million people in cotton growing. The industrial sector employs 1.0 million people. At present there are 3660 ginning and 1570 textile mills in India. India earns foreign exchange to a tune of Rs. 2500 million through exports of cotton textiles and products. Cotton is cultivated for ‘lint’ which is used for preparing threads, yarns and medical cotton mixed with synthetic fibre and for various other purposes.

A. Diseases

1. Bacterial Disease: Angular leaf Spot

Occurrence & severity status

Angular leaf spot disease, also known as ‘Black arm disease’ or ‘Bacterial blight’ is a disease of cotton potentially destructive in all cotton-growing areas of the world. The disease became prevalent in the USA during the 1950s (Schnathorst et al., 1960) and in India in the 1970s (Verma, 1986). In the USA, losses of between 34 and 59% were reported (Leyendecker, 1950; Bird, 1959). In India, losses of 5-20% were common in crops (Verma and Singh, 1971). Late and very late sowing of crops resulted in more yield reductions (Meshram and Raj, 1992). In general, losses due to bacterial blight in India are ranged between 1% and 27% depending on the cultivar and crop age (Mishra and Krishna, 2001). In Africa, data on crop losses is available for only a few countries. In Sudan, losses of 20% were common from severe infection (Last, 1960). However, nowadays, due to the wide availability of resistant varieties, its importance has been declined, with certain deviations where proliferation of new races has occurred as in Australia (Anonymous, 1980).

Introduction
 
Cotton belongs to the genus Gossypium, family Malvaceae. Of the 50 species, only four are cultivated, namely, G. arboreum, G. herbaceum, G. hirsutum and G. barbadense. The G. arboreum and G. herbaceum are popularly known as the desi cottons. The G. hirsutum and G. barbadense evolved in the new world and are known as American or Upland (G. hirsutum) and Egyptian or Pima (G. barbadense) cottons. India is the only country in the world where all the four cultivated species of cotton are grown on a commercial scale besides hybrids (both inter and intra specific) in three distinct agro-ecological regions and wide range of soil types.

Anthracnose
Diagnostic Symptoms
• Pathogen infects the seedlings and produces small reddish circular spots on the cotyledons and primary leaves.
• Lesions develop on the collar region, stem may be girdled, causing seedling to wilt and die.
• In mature plants, the fungus attacks the stem, leading to stem splitting and shredding of bark.
• Most common symptom is boll spotting. Small water soaked, circular, reddish brown depressed spots appear on the bolls.
• The lint is stained to yellow or brown, becomes a solid brittle mass of fiber.The infected bolls cease to grow and burst and dry up prematurely(Fig-2).
Etiology
Scientific Classification
Kingdom : Fungi
Division : Eumycota

I. FILL UPS

1. _____ is called as ‘king of fibres’ and ‘white gold’.
2. _____in the cotton meal is toxic to monogastric animals.
3. A purple spot is found in the claw of the petals is called _____
4. The isolation distance adopted for cotton is _____ for foundation seed.

The disease i s seen at all crop growing stages. The fi rst symptoms appear at the time of emergence of seedlings, when the cotyledons are attacked. They become yellow and turn brown followed by wilting and drying of the affected seedlings. In the fi eld, the wilting symptoms appear in patches. First of all, the older leaves become yellow, loose their turgidity, wilt, turn brown and droop.

This is the commonest symptom of nearly all respiratory diseases and is indicative of an effort to expel a foreign substance causing irritation on any place in the cough reflex path.

The center is in the medulla close to the respiratory centers. This is activated reflexly by the afferent impulses traveling up mostly along the vagus and to a less extent, the vagus and the phrenic (to bronchi and diaphragm), the spinal accessory, intercostals and other nerves supplying the accessory muscles of respiration. The peripheral fibres of the vagus and the phrenic are also sometimes directly affected causing cough reflex.

The medullary center itself may also be excited or restrained by impulses from superior cerebella centers, so that cough may be induced or controlled by voluntary efforts.

Counselling represents a purposeful, collaborative relationship between a trained professional and an individual seeking assistance with personal, emotional, psychological, or behavioral concerns. This helping relationship is founded on principles of trust, confidentiality, and mutual respect, creating a safe environment where individuals can explore their thoughts, feelings, and experiences without judgment. The American Counseling Association defines counselling as a professional relationship that empowers diverse individuals, families, and groups to accomplish mental health, wellness, education, and career goals. This definition emphasizes the empowerment aspect of counselling, highlighting its role in facilitating personal growth and development rather than simply addressing problems or deficits. The fundamental nature of counselling involves a systematic p

1.1. Introduction
The terms ‘counselling’ and ‘health promotion’ complement each other when it becomes a matter of an individual’s health. Health promotion is a part of behavioural social science that aims to change the systemic strategies adopted by the individual or group or by the mass community for the betterment of their health which can be achieved by talk therapy known as counselling. In the 21st century, from childhood to adulthood, all people are in a ‘rat race’ for their careers and necessities, which is one of the main reasons for stress generation. Not only that, chemical substances consumed by different food ingredients as food additives, preservatives, etc. but also induce oxidative stress and damage the functional activity of cells, tissues, organs, and systems. This ‘stress’ is a major culprit not only for the deterioration of physical health but also psychological health. Such stress imposition in daily life impairs normal physiological functions, skills, performance, and productivity. Unhealthy food, life, and work styles are also linked to the onset of pathophysiological complications that counselling and health promotion are required to overcome. Besides this, for sportsmen, pregnant women, lactating mothers, and growing children, nutritional counselling and health promotion are indisputable. For disease prevention and early recovery from disease, dietary counselling plays an immense role.
1.2. Counselling
Counselling is an intermittent, interpersonal interviewing process where the counsellor gives advice or suggestions to the client but never gives any direction. Counsellors assist the client in thinking, analysing, and acting to improve their insight power. The counsellor focuses on both the positive and negative sides of a particular event and allows the client to think and rethink its acceptability and unacceptability.

Enumeration of cells is essential to determine the multiplicity of infection, efficiency of plating and to obtain the specific number of cells for an experiment. The concentration of cells of a suspension can be counted using a haemocytometer. Each chamber is divided into a grid of nine large squares. Each large square is 1mmX1mm (area 1 mm²) and the depth is o.1 mm. The volume of each square is 0.1 mm³ or 10^-4 cm³. Since 1 cm³ is equal to 1 ml, the number of cells per ml of suspension can be obtained by multiply the average count per large square by 10⁴ and reciprocal of dilution factor. Dilution is made in such a way that one large square contain about 20-60 cells. The haemocytometer chambers should be filled by capillary action and cell clump are counted as one cell. A total count does not distinguish between living and dead cells. The number of viable cells can be determined by staining the cells with trypan blue or erythrosine B. In trypan blue staining cells appear as unstained whereas dead cells appear as blue.

5.1 Afghanistan Overview of the Agri-Food Economy Agriculture is a vital sector in Afghanistan, contributing around 25% to national GDP and employing nearly 60% of the workforce (World Bank, 2023). The country’s agro-climatic diversity enables the cultivation of staple crops such as wheat, along with high-value horticultural products like pomegranates, grapes, almonds, and apricots (FAO Afghanistan, 2022). Despite this potential, the sector is highly vulnerable due to climatic extremes, institutional fragility, and limited infrastructure. Key Challenges • Conflict-related Disruptions: Persistent conflict and political instability have disrupted agricultural activities and supply chain networks, undermining both domestic

31.1 Introduction

Courtship is the behavioural interaction that occurs between males and females before, during and just after mating. It encompasses all expressive movements associated with pair formation and mating. “Courtship is the heterosexual communication system that leads to the consummatory sexual act,” says DeMorris. Arthropods, mollusks, fish, reptiles, and mammals are the most affected. It consists of various activities and serves a specific purpose. Many courtship activities ensure that people only mate with people of their species. The distinction between species’ courtship behaviour allows females to identify males of their species. It is concerned with reproductive fitness and provides opportunities for survival

3.1. Conventional farming

Refers to the use of synthetic chemical fertilizers, pesticides, herbicides and other continual inputs, genetically modified organisms, heavy irrigation, intensive tillage and concentrated monoculture production.

Highly resource and energy intensive, but also highly productive.

Conventional farming typically involves monocropping, but very expensive.

Introduction

Modern intensive agriculture systems based on the principles of yield maximization have been plagued with multiple constraints such as declining factor productivity, decreasing resource use efficiency (fertilizers, water, labour etc.), soil organic matter decline, salinization, soil structure degradation, water and wind erosion, reduced water infiltration rates, soil compaction due to surface sealing and crusting, declining ground water table, pest and disease outbreak, weed resistance and weed shifts (Paustian et al., 2016). To address these overwhelming issue, conservation agriculture (CA) has been defined by FAO as a concept of resource saving agricultural crop production which is based on enriching the natural and biological processes above and below ground. The major purpose for its advancement is to reduce the production cost, save resources, enhance yields and utilize resources like nutrient and water efficiently. Conservation tillage denotes soil management system that follows the principle of at least 30% of the soil surface coverage with crop residues after seeding of the crop (Jarecki and Lal, 2003). CA, a resource-efficient agriculture helps to conserve, improve and utilize natural resources efficiently through integrated management of available soil, water and biological resourwces combined with external inputs and thus contributes to environmental conservation as well as enhanced and sustained agricultural production in the long term. The practice and wider extension of conservation agriculture thus requires a deeper understanding of its ecological underpinnings for managing its various elements for sustainable intensification.

ABSTRACT

Microbial contamination is perceived as the most serious threat faced by plant tissue culture research laboratories and commercial production units. A culture is often viewed as contaminated when obvious microbial growth incited by fungi, yeast or bacteria is noticed on the culture medium. On the other hand, there can be situations when microbes may be present in a covert or latent form with serious side effects on the cultures. The present investigations were taken up with the objectives of elucidating the cause of poor growth, lack of regeneration response or modification of rooting observed with visibly clean cultures of different horticultural crops. Apparently clean cultures of grape, banana, watermelon, eggplant, gerbera and chrysanthemum of recent origin or after long-term in vitro culturing were used in this study. Indexing the medium of such cultures using fungal/ yeast and bacteriological media brought out the covert association of one or more bacterial types with varying proportions of incidence in such cultures. Indexing of tissue revealed bacterial presence in different parts of in vitro plantlets. In some instances, bacteria showed endophytic colonization while being not detectable in the tissue culture medium subsequent to a disinfection or antibiotic treatment. Such bacterial association appeared to be the cause of in vitro decline observed with long-term micropropagated cultures, lack of reproducibility of tissue culture protocols, failure of in vitro rooting etc. besides being a threat to in vitro gene banks and germplasm exchange.

The manuscript was completed in February 2020. The book was supposed to be out in print form in April 2020. In between the pandemic changed the world. Obviously, world changing events can’t be left out of the book, particularly if the book is about the future of science, engineering, technology and humanity. I, therefore, requested the publisher of the book for the inclusion of a chapter COVID crisis and its impact on the future of the world. He readily agreed.

I am sincerely grateful to the publisher for allowing me to include issues relevant for the present book, as an additional chapter at the end of the book. The subject at the moment looks unending and it has so many dimensions. I have tried to cover them as briefly as possible, in the context of the book. In spite of the several difficulties due to this last minute inclusion the publisher has taken pains to include it. I am grateful to him for his gesture.

The pandemic of this proportion is expected to get the views/suggestions from equally large number of people. Everyone is eager to see the end of the pandemic. And everyone has realised that the world will be a much different place. Some people are hopeful that the problems will be resolved, of course using multi-dimensional approaches. Not many are sure of the time frame. There is also pessimism among common people. One of my aunt’s asks me - what kind of research we have been doing all these years that we can’t even face the challenges posed by a mere virus? Has the balloon of the technology busted by a miniscule virus? In this fluid time many questions are being asked, and as many answers are also emerging. It is a big issue. It is as big as that emerged after the Second World War. Some are calling it the ‘birth of a new power’.

Introduction The impact of COVID-19 on the fisheries and food industries of vary, and the situation is rapidly evolving. Fisheries products that are highly dependent on international trade suffered quite early in the development of the pandemic from the restrictions and closures of global markets, whereas fresh fish and shellfish supply chains were severely impacted by the closure of the food service sectors (e.g. hotels, restaurants and catering facilities, including school and work canteens). Although COVID-19 does not fish, the fisheries sector is still have indirect impact in the pandemic caused changing consumer demands, market access or logistical problems related to transportation and border restrictions (Purkait et al., 2020). This will in turn have a damaging the effect on fisheries and aquaculture farmers in livelihoods, as well as on their food security of the populations that rely heavily of the fish for protein and essential micronutrients. The processing sector also faced closures due to reduced/lost consumer demand. This has had a significant impact, especially on women, who form the majority of the workforce in the post-harvest sector (Avtar et al., 2021).

Cow Based Formulations describes traditional agricultural preparations made from cow-derived materials and other locally available ingredients for soil fertility, pest management, disease management, crop growth, and stress management. The chapter covers Ghana Jeevamrutham, Jeevamrutha, Amruthajalam, Amudham solutions, buttermilk-based preparations, and microbial formulations for improving soil fertility. It also presents Neemastram, Agniastram, Brahmastram, Dashparni Kashayam, and related preparations for pest management, followed by BeejAmrutham, Beejaraksha, herbal teas, and other disease-management inputs. Panchagavya, fish amino acid, egg amino acid, vermiwash, and cow dung–asafoetida solution broaden the discussion toward growth promotion and stress management in natural farming. using locally accessible agricultural resources today.