eChapters

ABSTRACT

Shivaliks, the most impor tant ecosystem of the foothills of the Himalayas, have been identified as one of the eight most degraded rainfed ecosystems of the country. They are characterized by undulating barren hill slopes, undulating agriculture fields and erratic rainfall pattern. Majority of the lands under cultivation and orchards in the hilly terrain of the state are thus subjected to runoff and soil loss of varying degrees. The soils of Shivalik hills in Solan district of Himachal Pradesh were found to be coarse in texture with abundance of gravels (upto 73.20%). According to the erodibility indices i.e erosion ratio (ER) and erosion index (EI), all the soils were found to be erodible; however, grasslands and forestlands recorded lowest values for these indices. Forest soils had higher water stable aggregates (WSA), mean weight diameter (MWD) and lower dispersion ratios than the cultivated and orchard soils. The dispersion ratio was comparatively higher under cultivated lands (17.37-22.54) followed by orchards (14.36-14.99) and lowest under forest soils (12.59-13.70). Areas having barren lands recorded very high soil loss (86.05 t ha^-1 yr^-1) followed by intensively cultivated areas (58.87 t ha^-1 yr^-1) and both of these have fallen in very high category of priority. A medium category of soil loss has been observed under degraded forests, agro-horticultural plantations and scrubs (14.77 – 18.27 t ha^-1 yr^-1). While low to very low soil loss was recorded under moderately dense, mixed and dense forests (3.46 – 9.59 t ha^-1 yr^-1). Weighted soil loss of 10.60, 17.12, 19.20 and 256.73 t ha^-1 yr^-1 was observed under 5-10, 10-15, 15-35 and >35 per cent slope classes. However, dense forests in all the slope classes registered annual soil loss within the tolerance limit (5 t ha^-1 yr^-1). Hence, maximum runoff, soil loss and available NPK losses were recorded from the barren lands and lands under cultivation followed by orchards and minimum under forests. Risk of soil erosion is higher on steeper slopes. Mixed forests in slope class of 15-35% have also reflected very high soil loss. However, dense forests in all the slope classes registered annual soil loss within the tolerance limit (5 t ha^-1 yr^-1). There is an urgent need to adopt suitable soil and water conservation measures to check runoff losses causing loss of soil and nutrients.

Vector data analysis is performed to convert raw input vector data to output that provides new and meaningful information which ultimately supports decision making and disclose hidden patterns. There are various techniques to analyse vector data like buffering, intersect, union, and so on. Some of the most commonly used techniques with their R-code examples are explained in this chapter.

First of all, you need to import all the packages which are required for performing this exercise. These packages include rgdal and sp for importing and re-projecting vector data as well as raster and rgeos for performing vector analysis operations.

The introduction of high yielding varieties, additional irrigation facilities, a great input flow through fertilizers and pesticides, farm mechanization, credit facilities and other rural infrastructure facilities ushered in the green revolution. The food grains area under irrigation as a percentage to its total sown area has been increased from 20.9 to 51.2%, rice irrigated area from 36.5 to 58.3%, wheat from 43.1 to 93.4%, pulses from 9.4 to 18.6%, oilseeds from 3.7 to 28.6% during the period from 1965-66 to 2013-14 (DES, 2015). Despite the net sown area being stagnant around 140.80 M ha, gross cropped area has been increased significantly from 155.28 M ha in 1965-66 to 195.25 M ha in 2011-12 due to increase in net irrigated area from 26.34 to 65.26 M ha (Fig. 1), gross irrigated area from 30.90 to 91.53 M ha during the period. There has been a sharp decline in average size of operational land holdings. The scope for expansion of the area available for cultivation has become limited. The average size of holdings for all operational classes (small & marginal, medium and large) have declined over the years and for all classes put together it has come down to 1.16 ha in 2010-11 from 2.28 ha in 1970-71. Therefore, it is the urgent need to use the natural resource like water efficiently and in a sustainable manner.

Animal and poultry feed and fodder production management is a vital aspect of the agricultural industry, playing a pivotal role in sustaining livestock health and productivity. This intricate domain encompasses a myriad of practices, technologies, and strategies aimed at producing high-quality feed and fodder to meet the nutritional needs of various animal species, ensuring their optimal growth, development, and overall well-being. Feed and fodder production management involves the cultivation, processing, and formulation of feed ingredients tailored to the specific dietary requirements of different animals. From traditional practices to modern, technology-driven methodologies, this field has evolved significantly to address the growing demands of an expanding livestock industry. The cornerstone of effective feed and fodder management

Processing of fruits  and vegetables into various products which could be preserved for a long time and add to value of product using proper cost effective technology will be a viable tool for improving   economic status of  farmer as well as our country. Modern methods of fruit and vegetable preservation are  broadly classified as follows:

Many aspects of the global climate are changing rapidly. Evidence for changes in the climate system abounds, from the top of the atmosphere to the depths of the oceans. The climate system is the highly complex system consisting of five major components; the atmosphere, the hydrosphere, the cryosphere, the land surface and the biosphere, and the interactions among them. The climate system evolves in time under the influence of its own internal dynamics and because of external forcings such as volcanic eruptions, solar variations and human-induced forcings such as the changing composition of the atmosphere and land-use.

The term ‘climate variability’ is often used to denote deviations of climatic statistics over a given period of time (e.g., a month, season or year) from the long-term statistics relating to the corresponding calendar period. In this sense, climate variability is measured by those deviations, which are usually termed anomalies.

‘Climate change’ refers to a statistically significant variation in either the mean state of the climate or in its variability, persisting for an extended period (typically decades or longer). Climate change may be due to natural internal processes or external forcings, or due to persistent anthropogenic changes in the composition of the atmosphere or in land use. The United Nation’s Framework Convention on Climate Change (UNFCCC) defines ‘climate change’ as ‘a change of climate behaviour which is attributed directly or indirectly to human activity that alters the composition of the global atmosphere and which is in addition to natural climate variability observed over comparable time periods’. The UNFCCC thus makes a distinction between ‘climate change’ attributable to human activities altering the atmospheric composition, and ‘climate variability’ attributable to natural causes. Climate change is a long-term shift in weather conditions measured by changes in temperature, precipitation, wind, snow cover, and other indicators. It can involve both changes in average conditions and changes in variability, including, for example, changes in extreme conditions.

A key difference between climate variability and change is in persistence of ‘anomalous’ conditions. In other words, events that are used to be rare occur more frequently, or vice versa. Occasionally, an event or sequence of events occurs that has never been recorded before, such as the exceptional tsunami in the Indian Ocean in 2004 or hurricane season in the Atlantic in 2005. Yet even that could be a part of natural climate variability. If such a season does not recur within the next 30 years, by looking back it could be called as an exceptional year, but not a ‘climate change’. Only a persistent series of unusual events taken in the context of regional climate parameters can suggest that a potential change in climate has occurred.

Q.1 In random effect model, the treatments are taken as a random sample of treatments drawn from a large group of T treatments.

Q.2 In varietal trials for plant breeding or genetics, the appropriate statistical model is not the random effect model.

Mutation breeding is a method that uses physical radiation or chemical means to induce genetic variation in plants to develop new crop varieties. Mutation can be defined as a sudden heritable change in the character of an organism which is not due to either segregation or recombination. Mutation is the source of most genetic variation and the motor of evolution. It is a natural process, which occurs spontaneously and slowly over generations in plants, animals and all living beings. It involves alteration of their DNA, leading to the development of changes within the organism. Mutation may be sped up through the treatment of physical or chemical mutagens to achieve alteration in characteristics that are useful for the development of new variety of a plant species.
Spontaneous mutations
Spontaneous mutations are the net result of all that can go wrong with DNA during the life cycle of an organism (Glickman et al., 1986). Thus, the types and amounts of spontaneous mutations produced are the resultant of all the cellular processes that are mutagenic and those that are anti-mutagenic. Spontaneous mutations occur naturally without any apparent cause however, there are two possible sources of origin of these mutations.

The calculation of raster data statistics is very essential before performing some geoprocessing operations. Raster data statistics involve knowing the distribution of pixel values in a band, comparing the pixel values of two bands, extracting values of all bands for a particular geographical location or point, and computing statistics like mean, median, standard deviation, etc. at pixel level across all bands of raster dataset.

In R, codes to perform raster data statistics are present in raster package. The visualisation of raster data statistics can be done by rasterVis package. So, we need to import these packages in R in order to perform this exercise.

I. General information

1. All cacti are succulents
2. All succulents are not cacti
3. All the genus belonging to the family Cactaceae are native of America
4. A genus in Cactaceae family which is not native of America is Rhipsalis
5. Sedum and Sempervivum are native to temperate Europe
6. Aporocactus, Rhipsalis and Schlumbergera are native of Mexico
7. Dischidia and Hoya are native of South-East Asia

INTRODUCTION

Fish live in a variety of watery habitats and comprise around 50% of all vertebrate species worldwide. There are approximately 21,723 known living fish species out of a total of 39,900 vertebrate species, with 8,411 found in freshwater habitats and 11,650 in marine environments (Jayaram, 1999). Fish are used as markers of contamination and contribute significantly to the preservation of human history and welfare, either directly or indirectly. According to Mittermeier et al. (1997), India ranks eighth in the world for freshwater biodiversity, making it one of the nations with significant biodiversity. There are over 2,500 fish species in India; roughly 930 of them are found in freshwater environments, and roughly 1570 are found in marine ones (Kar et al., 2006).

Fish diversity is particularly rich in the northeastern part of the nation; studies have shown that there are 267 freshwater fish species from 114 genera distributed over 38 families and 10 orders (Mahanta et al., 2003). Fish plays a crucial role in Assam's cuisine, where a wide range of fish species may be found in the region's floodplain wetlands because of the subtropical climate, favorable ecological and topographical circumstances, and inherent capacity for stocking. Assam's waters, including its wetlands, are home to around 217 fish species, representing 104 genera, 37 families, and 10 orders, according to Goswami & Singha (2023). Assam's lakes and marshes are vital for supplying the state's domestic fish needs, fostering economic growth, and giving the general public access to fairly priced food. In Maguri Beel, several fish are in danger of going extinct because of pollution, habitat damage, and the introduction of non-native species, overexploitation and human activity (Moyle & Moyle, 1995; Malakar & Boruah, 2017). The 2020 oil spill incident might have had a major impact on the variety of the ichthyofauna's composition. To address the same, a comparison of the same with earlier research is desperately needed. As a result, the current study intends to examine the fish variety of Maguri Motapung Beel, close to Motapung Village in the Tinsukia region of Assam and Dibru-Saikhowa National Park.

India has a substantial livestock population, with animal husbandry acting as a supplementary occupation for about 67% of the rural population. Unlike the commercially oriented farming systems found in Western countries, livestock rearing in India is intricately linked to rural life, where most farmers maintain a small number of animals.
Currently, India’s livestock population surpasses 535 million, which includes 192.49 million cattle, 109.85 million buffaloes, 74.26 million sheep, 148.88 million goats, 9.06 million pigs, and over 850 million poultry birds. Each year, approximately 100 million animals are slaughtered in nearly 4,000 slaughterhouses, resulting in a significant amount of by-products or offals. In tropical regions, a considerable portion of these by-products deteriorates before they can be utilized, primarily due to a lack of knowledge, skills, and infrastructure.
Enhancing profitability in the livestock sector could be realized through improved utilization of animal by-products and waste. Many slaughterhouses presently do not have sufficient facilities to collect and preserve these byproducts in a timely manner. Additionally, retrieving fallen animal carcasses from remote rural areas often presents challenges. The competitiveness of the meat industry can be bolstered by more effective use of by-products. It is estimated that by-products such as skin, pluck, head, feet, and gut can recover approximately 30% and 35% of the live animal value for goats and sheep, respectively. Thus, it is crucial to add value to significant by-products.

INTRODUCTION

Soil-borne pathogens cause heavy losses to most agricultural crops. Repeated planting of a crop in the same piece of land results in a high inoculum build-up, which forces the farmers either to change the crop or the land. Thus, the search for new, effective, inexpensive and non-hazardous methods for the control of soil-borne diseases is a continuous one. Over the years, efforts have been made to manage the soil-borne pathogens by employing fumigants, chemical pesticides, biological control agents, different type of soil amendments and also by causing modifications in different cultural practices. But, pathogen control is often hampered by the fact that both the inoculum of the pathogens and the lethal agents applied to the soil are affected by the soil’s physical, chemical and biological environment. Keeping in view the bottlenecks with different methods of management of soil-borne pathogens; harnessing of solar energy i.e. soil solarization is an effective method to control soil-borne pathogens.

Abstract

Bioinformatics is a field of science which studies biology, computer science, and information technology. The ultimate goal is to obtain useful information by data acquisition, analysis and interpretation of sequences data. In the current decade, a huge volume of sequence data is stored in the data bank due to global genome initiatives of many organisms. Management and understanding of the genome data cannot be possible without the bioinformatics tools. A large number of tools and softwares packages are available either commercial or freely online for the bioinformatics applications. The use of bioinformatics tools enhances the research capability for crop improvement through genome sequencing, database management, assembly, alignment, primer designing, markers development, genes prediction and annotation, gene expression, phylogenetics, protein structure identification, metabolic pathways analysis and many other applications.

Introduction

The finance sector is undergoing a profound transformation driven by technological advancements, with artificial intelligence (AI) and blockchain technology at the lead of innovation. AI, characterized by its capacity to analyze vast datasets, recognize patterns, and take data-driven decisions has revolutionized various industries, including finance. On the other hand blockchain technology, initially popularized by cryptocurrencies like Bitcoin has arose as a disruptive force in finance, offering decentralized, transparent and secure transactional systems.

The integration of AI and blockchain technology holds immense promise for the finance sector, offering new avenues for efficiency, transparency, and risk management. By combining the analytical power of AI with the security and transparency of blockchain, financial institutions can streamline operations improve customer experiences, and mitigate risks more effectively. However realizing the full potential of this integration requires a nuanced understanding of its complexities, challenges, and opportunities.

Genetic characterization using DNA markers is a cutting edge technology that makes it possible to study animal variability at basic level. A genetic marker can be any stable and inherited variation which is measurable or detectable by a suitable method and can be used subsequently to detect the presence of a specific genotype or phenotype other than itself, which otherwise is non-measurable of very difficult to detect. Such variations exist at morphology, chromosome, biochemistry or DNA levels that can serve as genetic markers. Molecular markers are the markers that reveal variations at the DNA sequence level. The polymorphisms observed at the DNA sequence has many applications which include percentage determination, genetic distance estimation and evolution, determination of individual identity, identification of disease carrier (heterozygous) animals, determination of twin zygosity and freemartinism, gene mapping, marker assisted selection (MAS), sex determination, DNA fingerprinting and transgenic breeding. Gene mapping is a tool to identify the genes responsible for specific traits.  The genetic map is constructed from linkage relationship based on the frequency of meiotic exchange (amount of recombination) among linked traits. Genetic map helps

A. Agronomic Considerations for Good Experimentation

For laying out of any experiment (Short / long term) at on-station and on farmers field, some of the agronomic considerations are very important for better results using experimental designs. Therefore, these are discussed here in this chapter.

1. Cropping History

The crop performance and its yield is affected by the crop grown and management followed during previous years. Therefore, for meaningful interpretation and factual reflection on yield trend due to the treatment proposed to be evaluated, the details of crop grown during previous 2 years/ seasons with details of management followed especially input applied needs to be recorded.

The human civilization and environmental eco-system are the two most important components of real world. The technology intervention to safeguard human civilization and the environment has always been the foremost priority of scientific and engineering community through their innovative expeditions.

15.1 Introduction

An endoskeleton is a skeleton that is on the inside of the body of an animal. It is an internal supporting structure composed of mineralized tissue. The endoskeleton develops within the skin or the deeper body tissues. It participates in protection, helps in movement, provides shape and support and stores minerals like calcium. Gerringer et al. (2021) suggested that changes in skeletal structure are non linear and are driven by hydrostatic pressure, other environmental factors and evolutionary ancestry.