eChapters

8.1. Introduction

Sometimes writing reference list could be so confusing since there are a lot of different rules. Each universities or even each faculty use different rule in writing reference list. The different rule of writing reference list is normal because they refer to different style guide. There are a lot of styles guide available. MLA (Modern Language Association of America) style; the Chicago Manual of Style; the Oxford Guide to Style are some examples of style guide. Difference reference of style guides chosen will result in totally different way of writing reference list. The most widely accepted style guides in social science is the APA (American Psychological Association) style. In some higher education journals (e.g. Journal of Studies in International Education, Higher Education) it is stated clearly that author must submit their paper according to APA style. Referencing in a general sense means to give credit to someone for using his or her own ideas or thoughts in a research activity. Referencing helps in gaining the originality of the ideas and thoughts used in the research activity. Failure to reference is treated as disrespect to the original author or writer and seen as a major misconduct in the area of academic research writing. Generally students made the mistake of not mentioning proper referencing at the end of their research projects, essays or any other piece of work. This may lead to cancellation of the written matter. If we do not reference properly the written matter is treated as if it is copied from somewhere. The research paper or material cannot be submitted for further research or reading purpose. We find a lot of data when we search for something.

7.1. People’s Participation in Observation, Analysis and Planning for Rural Development

Why should people participate?

There is no controversy as to whether there should be people’s participation in the development programmes in the development programmes designed to meet the basic needs of the people. The post-mortem of any unsuccessful programmes has shown that they have invariably failed when they failed to provide an adequate place and importance to people’s participation in the planning and analysis.

There is a body of philosophy and a set of assumptions behind people’s participation in rural development. These are;

i) It should be people’s programme with government’s participation;

ii) Community needs to build up their own capacity, agents have got a catalytic role;

iii) Self- imposed changes have got permanence as compared to those imposed from outsides

iv) Holistic approaches are far better than the fragmented approaches;

v) People need certain help to solve unique problems;

Statistics as a wide subject is used in almost all disciplines especially in research studies. Statistics provides scientific tools for representative data collection, appropriate data analysis and summarization of data and inferential procedure for drawing valid conclusion in the face of uncertainty. Each and every researcher should have some knowledge in Statistics and must use statistical tools in his or her research, one should know about the importance of statistical tools and how to use them in their research or survey. The quality assurance of the work must be dealt with: the statistical operations necessary to control and verify the analytical procedures as well as the resulting data making mistakes in analytical work is unavoidable. The emergence of statistical software in the twenty-first century has helped different researchers in the physical and social science to improve in the quality of research. Most renowned researchers in adopting this software in their data analysis have been able to identify the immense contribution to research findings (Adetola, 2013). Any quantitative research cannot be done effectively without Statistical Software. Moreover, it enables research data for easy presentation. It helps professionals to interact with data thereby paving way for creativity and innovation. Some are user friendly interface with drop-down tips for beginners (ATS, Ucla Edu, 2014). Advances in technology have improved all our lives (Akindutire, 2013) and has allowed experts greater freedom to come out with results within a twinkle of an eye than ever before where it takes time to finish analysis. This same technology has offer tremendous opportunity to research and keep research as a more interesting field of study. This study is significant, because it is an attempt to measure the direct impact of different statistical software on research analysis.

A linear programming problem aims to maximize or minimize a linear function subject to the linear constraints. But in many cases, the objective function may not be linear or all/some of the constraints may not be linear or both the objective and the constraints may not be linear. Such an optimization problem is called a nonlinear programming problem (NLPP). In this chapter, we discuss about NLPP’s. Nonlinear programming is the process of solving an optimization problemdefined by a system of equalities and inequalities, collectively termed constraints, over a set of unknown real variables, along with an objective function to be maximized or minimized, where some of the constraints or the objective function are nonlinear. It is the sub-field of mathematical optimization that deals with problems that are not linear. A typical non-convex problem is that of optimizing transportation costs by selection from a set of transportation methods, one or more of which exhibit economies of scale, with various connectivity and capacity constraints. An example would be petroleum product transport given a selection or combination of pipeline, rail tanker, road tanker, river barge. Owing to economic batch size the cost functions may have discontinuities in addition to smooth changes. In experimental science, some simple data analysis (such as fitting a spectrum with a sum of peaks of known location and shape but unknown magnitude) can be done with linear methods, but in general these problems, also, are nonlinear.

Multivariate analysis is essentially the statistical process of simultaneously analyzing multiple independent variables with multiple dependent (outcome or criterion) variables using matrix algebra. During the last two or three decades, multivariate statistical analysis has become increasingly popular. The theory has made great progress, and with the rapid advances in computer technology, routine applications of multivariate statistical methods are implemented in several statistical software packages. The traditional approach to the teaching of multivariate statistical analysis, as exemplified by Anderson (1958), relies heavily on advanced matrix mathematics. On the other hand, Hury and Riedwyl (1988) suggest that it is possible to understand most of the basic ideas underlying multivariate statistical analysis without a mastery of such mathematics, provided that these are conveyed with the help of real data sets. In this chapter we propose a non-mathematical data-driven approach for teaching multivariate statistical methods to students. Despite this, we are mindful of the need for students to know some basic linear algebra and univariate statistical concepts. Such basic knowledge provides students with the foundation necessary for the application of the appropriate multivariate statistical procedures and for the interpretation of results.

In statistics, sampling is concerned with the selection of a subset of individuals from within a statistical population to estimate characteristics of the whole population. Two advantages of sampling are that the cost is lower and data collection is faster than measuring the entire population. Each observation measures one or more properties (such as weight, location, colour) of observable bodies distinguished as independent objects or individuals. In survey sampling, weights can be applied to the data to adjust for the sample design, particularly stratified sampling. Results from probability theory and statistical theory are employed to guide the practice. In business and medical research, sampling is widely used for gathering information about a population. Acceptance sampling is used to determine if a production lot of material meets the governing specifications.

The sampling process comprises several stages

• Defining the population of concern

• Specifying a sampling frame, a set of items or events possible to measure

• Specifying a sampling method for selecting items or events from the frame

• Determining the sample size

• Implementing the sampling plan

• Sampling and data collecting

Statistics is a branch of science which deals with the collection, classification, description and interpretation of data obtained by conducting surveys and experiments. The essential purpose of it is to describe and draw valid inferences about numerical properties of populations” (Ferguson 1966). The experience in statistics application indicates that a single statistical method can be used in different research areas for dealing with different types of problems. Various possibilities which application of a statistical method provides in certain research areas should be considered as an adequate way of dealing with a problem of the research. However, it should be noted that statistics is not a method by which it is possible to solve all the problems in a research. Nachmias and Nachmias (2009) stated that there are basically two types of statistics which include descriptive and inferential statistics. Descriptive statistics enable the researcher to summarize and organize data in an effective and meaningful way. It involves the use of tables, charts, graphs, mean, modes, median, standard scores and correlation to treat collected data. Inferential statistics is concerned with making inferences from a unit of a population. Inferential statistics is concerned with making inferences from a unit of a population. Inferential statistics allow the researcher to make decisions or inferences by interpreting data patterns. Researchers use inferential statistics to determine whether an expected pattern designated by the theory and hypotheses is actually found in the observations. To decide whether this hypothesis is true, researchers might survey the respondents and then use descriptive statistics to make comparison between these groups and would employ inferential statistics to determine whether the differences between the groups are significant or not.

1.1. Introduction

Research in simple terms refers to search for knowledge. It is a scientific and systematic search for information on a particular topic or issue. It is also known as the art of scientific investigation. Several social scientists have defined research in different ways.

In the Encyclopaedia of Social Sciences, D. Slesinger and M. Stephenson (1930) defined research as “the manipulation of things, concepts or symbols for the purpose of generalizing to extend, correct or verify knowledge, whether that knowledge aids in the construction of theory or in the practice of an art”. According to Redman and Mory (1923), research is a “systematized effort to gain new knowledge”. It is an academic activity and therefore the term should be used in a technical sense. According to Clifford Woody (Kothari, 1988), research comprises “defining and redefining problems, formulating hypotheses or suggested solutions; collecting, organizing and evaluating data; making deductions and reaching conclusions; and finally, carefully testing the conclusions to determine whether they fit the formulated hypotheses”

Introduction

Climate change has brought about unprecedented weather variability, disrupting established patterns and posing significant challenges to global agriculture. The Intergovernmental Panel on Climate Change (IPCC) reports unequivocal evidence of increasing temperatures and altered precipitation patterns (IPCC, 2021). These changes impact crop production, water availability, and overall food security, necessitating innovative approaches to ensure sustainable agriculture in the face of evolving climatic conditions. To address these challenges, accurate crop yield forecasting becomes paramount. Reliable predictions empower farmers, policymakers, and agricultural stakeholders to make informed decisions regarding resource allocation, risk management, and adaptation strategies (Lobell et al., 2012; FAO, 2019). This chapter explores the intricate interplay between weather variability, climate change, and the development of effective crop yield forecasting models, offering a comprehensive perspective on how sustainable agriculture can be achieved in the midst of these dynamic environmental shifts.

Introduction

Water is a prominent element in the daily life of human beings as well as in agriculture. In better crop production, the quantity of water, but the quality of water is also important. With respect to the current scenario of water harvesting or water conservation there are some techniques adopted in Indian agricultural practices, such as the use of drip irrigation to minimise water surplus, rain fed agricultural practices, storing rain water in different storage components, using mulching (either natural or plastic), proper tillage practices, selecting crops which need less amount of water, using laser leveller for better water uses to encounter surplus water flow to the lower elevated portion of the field etc. Water conservation techniques and measures are directly related to the type of meteorological factors of specific watershed. For the arid and semi arid regions proper method of tillage practice improves water use while in conventional practices of farming consumes more than required water quantity. Some crops are water-intensive where the quantity of the available water is crucial. Sources of water can be ground water, rain water and irrigation water. In sustainable crop production, the right amount of water is necessary for the optimal physiological growth of specific crops. Although the availability of water depends upon the geographical location, for example in the Gangetic plains of India there is less need for water conservation agricultural purposes. On the other, in the region of Deccan Plateau of India, availability of water is comparatively lower than in the Gangetic plains. It is also important that water conservation techniques can be adopted irrespective of the geographical locations. Water is conserved in nature itself but the availability of water depends on the hydrological cycle. Therefore, conservation has become a trending topic. Water conservation can be improved through sustainable agricultural practices such as proper scheduling of irrigation, selection of crops based on sustainability, monitoring soil moisture content, maintaining records of crop growth and physio-chemical data, implementing effective drainage systems, intercropping operations and utilising recycled water for other purposes.

Introduction

Soil fertility is a key factor in successful crop production measures the ability of the soil to supply nutrients to plants. Soil fertility and fertilisers are closely related concepts. Soil fertility acts as a "SOURCE" from which plants can absorb nutrients for maximum yield, while manure acts as a "SOURCE" from which we can continuously absorb various nutrients and also add to the soil. The importance of soil fertility and fertiliser management has been increasingly recognised in all countries to meet the demand for food and other agricultural commodities. Intensive use of fertilisers and cultivation of high yielding varieties has undoubtedly increased food production and reduced food scarcity, but it has also brought with it a host of problems related to soil fertility, soil and water pollution (Sow et al., 2023a). On the other hand, rapid depletion of nutrients due to overuse, widespread N, P, K, and S deficiency, along with micronutrient deficiencies, especially Zn and Boron, have been observed in many soils.

Introduction

According to the United Nations (UN, DESA 2019) the world population will reach around 9.7 billion by 2050. The Food and Agriculture Organisation (FAO) has predicted that the world food grain production must increase by 70% by the year 2050 to feed this ever-growing population (Bernard et al., 2017). United Nations World Population Prospects (2022) also predicted the same (Fig 1). However, it is a matter of great concern that the global food grain production has not increased to any significant level (Fig 2) in the past 15 years. As seen in Fig 2, the global food grain production trend has reached a plateau. The main reason behind this fact is the degradation of this valuable natural resource (soil) beyond the tolerance limit due to anthropogenic activities such as imbalanced fertiliser use with the application being largely skewed in favour of nitrogen (N) fertilisers. As per the available data from 2020-21, in nutrient terms, India consumes a total of 32.5 million tonnes (Mt) of fertilisers swhich are distributed over a stable net cultivated area of 141 million hectares (Mha) (Singh et al., 2022). Associated with this is the expenditure of a huge amount of energy for producing these fertilisers, which principally comes from fossil fuel burning, pumping a gigantic quantity of groundwater to solubilise these fertilisers and so on. Not only nitrogen, but the usage of phosphatic and potassic fertilisers has also witnessed an upsurge in the last 50 years (Fig 3).

Introduction

The importance of soil in agriculture cannot be overstated, as it serves as the foundation for crop growth and sustenance. However, many regions grapple with problematic soils characterised by issues such as poor fertility, erosion, contamination, and structural degradation. In recent years, significant steps have been made in addressing these challenges through innovative approaches and technologies. This change in outlook includes the combination of imaginative advancements, protection procedures, and biological standards to enhance farming efficiency while limiting ecological effects (Singh et al., 2011).

Farmers are challenged with the management of problematic soils characterised by fertility issues, erosion, contamination, and structural degradation. Sustainable agricultural techniques depend on the efficient management of problematic soils, which is also critical to environmental sustainability, global food security, and farming systems' ability to withstand climate change. The idea of changing soil and harvest management practices a complex system that incorporates accurate horticulture, agroecology, and computerised cultivating innovations (Fu et al., 2021).

Introduction

Agriculture faces a massive challenge: by 2050, it needs to sustainably feed over 9 billion people while supporting economic growth and protecting the environment. Meeting this demand requires a staggering 70% increase in food production from 2006 levels, mainly by making the most of existing farmland and resources.

Precision agriculture offers a promising way forward. It's about smartly managing soil and crops using technology and information to boost profits while being eco-friendly. This approach involves giving the precise amount of resources—like water, nutrients, and pesticides—at the right time and place to optimise farming. It's all about understanding and using the differences within f ields to improve crop growth and protect the environment. Traditionally, understanding these differences involved collecting tons of soil and plant samples for lab analysis. But this can be costly. So, finding better, more efficient ways to assess these differences in soil and plant growth is crucial.

Precision agriculture relies on high-tech tools like GPS, GIS, yield monitors, and remote sensing to measure differences in soil and crop growth across f ields. By integrating these technologies with tools that adjust resource usage based on these differences (called variable rate technologies), farmers can apply fertilisers and water precisely where they're needed, optimising crop yields (Ranjan et al., 2022a). This method has three main parts: collecting data, understanding that data, and then making smart decisions based on it, all tailored to specific areas and timings. New technologies like yield monitors, satellites, and handheld sensors have made data collection faster and easier. But the real challenge is making sense of all this information and using it effectively for better farming. This review delves into how these technologies can enhance agricultural production and the hurdles they bring.

Introduction

Agrochemicals are categorised based on the specific target organisms they are intended to control, including insects, weeds, and fungi. Among these target organisms, weeds significantly contribute to the highest economic losses due to their interference in crop production. Herbicides, the predominant class of agrochemicals globally, account for 48% of the total expenditure. The largest consumers of agrochemicals are Europe, Asia, and the United States. Herbicides have various biological and chemical properties (Roy et al., 2023a). They exhibit variations in behaviour and spectrum weed control. These properties play an important role in herbicide selection, method of utilisation and application, post-application effects such as toxicity and residue accumulation in the soil. The crucial factor for any herbicide application is the behaviour of the herbicide in the soil and its transformation or modification once it reaches the soil (Miller and Westra, 1914). The fate of herbicides and their efficiency are regulated by herbicide properties, soil characteristics and climatic conditions.

Introduction

Plant Parasitic Nematodes (PPN) belonging to the kingdom Animalia are considered the most serious threat to agriculture and horticulture crops worldwide. The estimated yield loss on average is about 173 billion USD (12.3%), among which developing countries are more prone to nematode infestation (14.46%) than developed countries (8.8%). Nevertheless, these PPN aggravate the loss by forming disease complexes with other soil-borne pathogens (Jones et al., 2013). PPN gain entry onto the host roots through their secretome which secretes various kinds of proteins that are mandatory for the expression of disease symptoms in host plants. These proteins are generally called Nematode-Associated Molecular Patterns (NAMPs). The management of nematodes through synthetic nematicides paves the way for the production of commodities with toxic residues that may have severe ill effects after consumption. However, the use of resistant plants is another strategy to combat major PPN and suppress their population in soil and roots. Recent research progress has revealed the various defence mechanisms exhibited by plants against the invasion of PPN. Here we will discuss in brief about the various mechanisms followed by the host plants to recognise the invading PPNs and the resulting host immune response in response to recognition of various effector proteins of PPN.

Introduction

Millet is a small grain cereal grass bearing coarse seeds, and since ancient times has been considered a valuable and nutritious grain. It includes jowar, bajra, ragi and small millets. Small millets include Barnyard millet, proso millet, kodo millet, little millet and foxtail millet. It is rich in fiber, protein, iron, calcium, magnesium, zinc, vitamin B, has a low glycemic index and has antioxidant, anti-inflammatory and anti-allergic properties (Ranjan et al., 2023). These have been added to the modern lifestyle as healthy foods because they are beneficial for human health due to the presence of nutritional ingredients. The nutritional quality of food is the most important parameter for maintaining human health and comprehensive physical health. Good nutrition is the driving force for growth and maximisation of human genetic potential (Radhila et al, 2011). Food quality in the diet must be considered to maintain optimal human health and fitness to address the deep-seated problem of malnutrition. Diversification of food production at both the national and household levels should be encouraged, in addition to increasing domestic productivity and technology (Singh and Raghuvanshi, 2016). Some agricultural foods are not used by humans as staple foods due to human ignorance. Millet is one of them. Millet is used as food for animals and birds. Millet has many nutritional and medical functions (Yang et al, 2012).

Introduction

Embarking on the journey of legume cultivation in India reveals a nuanced landscape marked by both challenges and promising horizons. The agricultural scenario is akin to orchestrating a symphony, where legumes play a vital role, contributing melodies of resilience and significance. Unveiling this leguminous symphony in India is an exploration into the intricate interplay of obstacles and potential triumphs within the agricultural sector. As we delve into an overview of legumes, commonly known as pulse crops, their significance in Indian agriculture becomes apparent. Belonging to the Fabaceae family, these plants possess a distinctive feature - the ability to harness nitrogen from the atmosphere. This unique characteristic renders them pivotal components in sustainable agricultural systems, impacting not only food and nutritional security but also influencing the broader scope of soil fertility enhancement and economic prosperity. The journey through legume cultivation in India unfolds as a harmonious narrative, weaving together the challenges faced and the promising prospects that lie ahead in this agricultural symphony (Sow and Ranjan, 2021).

Introduction

Throughout their existence on this planet, human beings have adapted to the diverse environments they inhabit. Depending on the topography and prevailing natural conditions, individuals have successfully navigated the challenges posed by nature and their surroundings. As life has progressed, humans have gained insights into nature, its resources, and the prudent utilisation thereof. This understanding encompasses various natural phenomena, the associated challenges, and the methods to mitigate them. Over time, humans have evolved into repositories of such knowledge, collectively known as 'indigenous knowledge' or 'traditional wisdom,' passed down from one generation to the next. Each specific region possesses its unique set of indigenous knowledge reflecting the harmonious coexistence of humans with their environment.

Indigenous agricultural knowledge (IAK) stands as a crucial force in the realm of agricultural development. It represents a systematic and collective body of knowledge, practices, and beliefs that evolve through adaptation processes and are transmitted across generations through cultural channels, elucidating the intricate relationship between living beings and their environment. With this collective wisdom, farmers have adeptly cultivated food crops in diverse environmental conditions and seasonal variations, relying on indigenous techniques in the absence of external inputs, resources, and scientific knowledge. This includes refraining from the use of synthetic agrochemicals and instead embracing practices like crop rotations and soil fertility restoration through closed nutrient cycles (Melash et al., 2023).

Introduction

The realm of agricultural policies and environmental policies stands as two critical pillars influencing the sustainability and equilibrium of our ecosystem. Agricultural policies primarily focus on regulations and measures instituted by governments or institutions to manage agricultural practices, production, distribution, and rural development. Conversely, environmental policies aim to safeguard and conserve natural resources, biodiversity, and ecosystems while mitigating the adverse impacts of human activities on the environment.

Overview of Agricultural and Environmental Policies

Agricultural policies often encompass subsidies, price controls, land use regulations, and trade agreements aimed at bolstering agricultural productivity, ensuring food security, and supporting rural economies (Fischer & Edmeades, 2010). Conversely, environmental policies encompass a broad spectrum of regulations, such as pollution control measures, wildlife protection, habitat conservation, and climate change mitigation strategies (Boyd & Banzhaf, 2007).

Importance of Understanding Their Interactions

Understanding the interactions between agricultural and environmental policies is crucial due to their interconnectedness and potential trade-offs. Agricultural activities significantly impact the environment through deforestation, water pollution from agricultural runoff, greenhouse gas emissions, and loss of biodiversity (Pretty et al., 2008). Conversely, environmental conditions greatly influence agricultural productivity and sustainability, including soil quality, water availability, and climate patterns. Recognition of these interdependencies is vital for devising coherent policies that foster sustainable agricultural practices without compromising environmental integrity (Tilman et al., 2011). The challenge lies in formulating policies that strike a balance between agricultural production goals and environmental conservation imperatives.