eChapters

Introduction

Soil, a dynamic living matrix, is an essential part of the terrestrial ecosystem. It is a critical resource not only to agricultural production and food security but also to the maintenance of most life processes. Soils contain enormous numbers of diverse living organisms assembled in complex and varied communities ranging from the myriad of invisible microbes, bacteria and fungi to the more familiar macro-fauna such as earthworms and termites. The diversity in soils is several times higher than that above ground. Each hectare top soil contains approximately 1,000 kg of different fungi, 500 kg of bacteria, 750 kg actinomycetes and 150 kg of algae and many protozoa (Table 1). These diverse micro-organisms interact with one another and with the plants and animals in the ecosystem forming a complex system of biological activity. Environmental factors, such as temperature, moisture and acidity, as well as anthropogenic actions, in particular, agricultural practices affect soil biological communities and their functions to different extents. Diversity of soil micro-organisms has emerged in the past decade as a key area of concern for sustainable soil health and crop production. Besides, the well-being and prosperity of earth’s ecological balance, the sustainability of agricultural production systems directly depends on the extent and status of microbial diversity of soil.

Introduction

Drought is the most important abiotic factor that adversely affect growth and crop production. Drought stress can altered the normal physiological processes that influence one or a combination of biological factors for yield and yield attributing traits (Ashraf, 2010). The abnormal metabolism due to stress may reduce plant growth (Claves et al., 2002). Production is limited by environmental stresses, according to different scholar estimates, only 10 per cent of the world’s arable land is free from stress, in general, a major factor in the difference between yield and potential performance, environmental stresses. Drought is one of the most common environmental stresses that almost 25 per cent of agricultural lands for agricultural farm products in the world are limited (Loresto, 1976; Chaves, 2002). Drought occurrence in India is also very frequent. Drought occurred in past 1967, 1968, 1969, 1972, 1974, 1979, 1987, 2002, 2009 and had considerable impact on food grain production. For example, the drought of 1966-67 reduced overall food grains production by 19%. The drought of 1972-73 reduced the food grains production from 108.95 million tonnes to 95 million tonnes, causing a loss of about $ 400 million $. The 1987 drought in India damaged 58.6 million ha of cropped area affecting 285 million people (Ray et al., 2015). Drought in 2002 has reduced food grains production to 174 million tonnes from 212 million tonnes resulting in decline of 3.2% GDP (Rathore et al., 2009; Ray et al., 2015).

The water deficit reduces crop yield due to decrease in photosynthetic area, decreased radiation use efficiency and harvest index (Earl and Davis, 2003). Drought stress affect the water balance and plant metabolisms. Plants under drought conditions use various changes to tolerate stress conditions and increase drought tolerance which includes changes in whole plant, tissue, at physiological and molecular levels. Appearance of a single or a combination of inherent changes determines the ability of the plant to stand under aridity conditions. Tolerant plant adjusts its water balance by osmotic adjustment, deep root systems and by transient leaf rolling.

Introduction

Soils are formed by weathering of rocks and minerals and all soils contain some amount of soluble salts. Many of these act as a source of essential nutrients for the healthy growth of plants. However, when quantity and quality of salts in the soil near rhizosphere exceeds a particular value, growth, yield and/or quality of most crops is adversely affected. Such a soil is called salt-affected. The degree of adverse effects depends upon the type and quantity of salts, crop and its variety, stage of growth, cultural practices and environmental factors viz. temperature, relative humidity, and rainfall etc. Development of salinity and waterlogging is a serious problem in arid and semi-arid regions of the world and threatening the sustainability of irrigated agriculture.

Salt-affected soils occupy an estimated 952.2 million ha of land in the world that constitutes nearly 7% of the total land area and nearly 33% of the potential arable land (Dudal and Purnell, 1986). In India, the salt affected soils account for 6.727 million ha i.e. 2.1% of geographical area of the country. These soils are mostly found in the states of Uttar Pradesh, Haryana, Punjab, Madhya Pradesh, Bihar and Andhra Pradesh. In the last 25 years 1.1 million ha of alkali soils have been reclaimed in the states of Haryana, Punjab and Uttar Pradesh. These have contributed to the additional food grain production of 10 million tonnes annually. Reclamation of alkali soils have also decreased the incidents of floods and malaria and increased the groundwater recharge.

Introduction

The Indian Himalayan Region (IHR), with geographical coverage of over 5.3 lakh km², constitutes a large proportion of the hotspot and, therefore, contributes greatly to richness and representativeness of its biodiversity components at all levels. Out of this 5.3 lakh km², 33.13 million ha area is being constituted by the North-Western Himalayas.^. Further, most of the water used to grow maize crop in the sub-humid foothill region of northwest Himalayas, is derived from rainfall. Erratic rains, fragile ecosystems and traditional indigenous management practices are mainly responsible for the current situation (Kukal and Bhatt, 2010). IHR covers 11 states entirely (i.e. Jammu & Kashmir, Himachal Pradesh, Punjab, Uttarakhand, Sikkim, Arunachal Pradesh, Nagaland, Manipur, Mizoram, Tripura, Meghalaya), and two states partially (i.e. hilly districts of Assam and West Bengal). The region represents nearly 3.8% of total human population of the country and exhibits diversity of ethnic groups which inhabit remote terrains. Further it is reported that the Northwestern Himalayan region (NWHR) which spreads to an approximate area of 33.13 million ha, comprising of Jammu & Kashmir, Himachal Pradesh, Uttarakhand is 10.1% of country’s total geographical area, supports 2.4% and 4% of human and cattle population of the country, respectively. This region has a diverse climate, topography, vegetation, ecology and land use pattern. The annual average rainfall varies from 80 mm in Ladakh to over 200 cm in some parts of Himachal Pradesh and Uttarakhand. The major natural resources are water, forests, floral, and faunal biodiversity. Forests constitute the major share in the land use of the region with only 15% of the net sown area and 162% cropping intensity (Bhatt, 2011).

Introduction

Farm mechanization is application of machine power to work on land, usually performed by animate and mechanical power. It is also defined as an economic application of engineering technology to increase the labour efficiency and productivity. However, it not only includes production, distribution and utilization of a variety of tools, machinery and equipment but also planting, harvesting and primary process. Mechanization has a major impact on demand and supply of farm labour, agricultural profitability and a change in rural dynamics.

Introduction

Worldwide, salt–affected areas are estimated to range from 340 million ha to 1.2 billion ha (FAO, 2007; Oo et al., 2015; Ahmad et al., 2016; Drake et al., 2016). Millions of hectare of these salt affected soils are suitable for agricultural production but are unexploited because of salinity/sodicity and other soil and water related problems (Abrol et al., 1988). Salt-affected soils are reported to comprise 42.3% of the land area of Australia, 21.0% of Asia, 7.6% of South America, 4.6% of Europe, 3.5% of Africa, 0.9% of North America and 0.7% of Central America (El-Mowellhey, 1998). In India, out of 329 million ha geographical land area of the country about 175 million ha suffers from different problems and is getting further degraded through natural or man-made processes. Majority of these lands is treated as wastelands as their productivity is low due to soil based constraints like water logging, salinity and sodicity. According to FAO, salinization of arable land will result in 30% to 50% land loss by the year 2050 if, remedial actions are not taken. Recent estimates indicate that 6.73 million ha (NRSA and Associates, 1996) land is suffering from salinity and sodicity problems in India. High salt deposits inherited by the soil from the original parent material during soil forming processes and poor drainage are important factors contributing to the development of such soils. These lands occur in different biogeographic zones and therefore consist of diverse morphological, physical, chemical and biological properties. These soils are universally low in fertility and due to the adverse edaphic environment; they are devoid of any vegetation because of excessive exchangeable Na+ associated with high pH (>8.5) which impairs the physical condition of the soils and adversely affects water and air movement, nutritional and hydrological properties of the soils (Suarez et al., 1984; Gupta and Abrol, 1990; Sumner, 1993; Garg, 1998).These lands are largely carbon-depleted but can be brought back to their native carbon-carrying capacity by reforestation through agroforestry systems. The presence of CaCO3 concretions at various depths (caliche bed) causes physical impedance for root proliferation, therefore, making it difficult for tree establishment and restrict the choice of arable crops to be grown (Shukla et al., 2011; Singh et al., 2012a).

Introduction

Livestock is an important component of Indian agriculture contributing 28% of agricultural gross value added (GVA) of the country. Agriculture, as such, contributes 16.4% of country's GVA (Economic survey, 2017-18). Livestock as a source of income has seen a steady increase from 4% to 13% in a decade time (2002-2012). India, with 2.29% of the world land area, is maintaining about 10.71% of the world’s livestock population. The milk production in the country increased from 17 million tonnes in 1950-51 to 187.7 million tonnes in 2018-19. The feed and fodder play an essential role in the health and productivity of livestock. Even though India is the world largest milk producer with 21% of global production, the productivity (1700 kg/year) is far below the world average (2574 kg/year) (FAO STAT, 2018). One of the main responsible factors (50.2%) for this low productivity is the deficiency in feed and fodder. Although forage crops are the critical component of livestock-based farming system, the area under cultivated fodder is static to around 8.4 million ha (5.23%) since last two decades due to the competition of land use with other crops. Availability of the fodder determines the productivity and profitability of the livestock rearing because fodder and feeds constitute about 60% of the total cost of milk production, which can be lowered by enhancing the green fodder-based feeding system. The traditional grazing lands are gradually diminishing because of urbanization, expansion of the cultivable area, grazing pressure, industrialization etc. These factors coupled with stagnation of area under cultivated fodder resulted in a severe shortage of feed and fodder to the extent of 26% in dry crop residues, 35.6% in green fodder and 41% of concentrates (IGFRI, 2011). This gap in demand and supply may further rise due to consistent growth of livestock population at the rate of 1.23% in the coming years. The share of the in-milk population to total population has increased from 23% to 27% in the case of cattle and from 33.64 to 34.74% in buffaloes from 2012 to 2019. The year-on-year growth rate of milk is approximate 6%. Thus, to sustain this growth rate and for further expansion to meet the demands of the ever growing human population, livestock needs a sustainable supply of feed material. To reduce the demand and supply gap, the production and productivity of fodder crops need to be enhanced. The productivity of cultivated fodder crops is low, due to the least attention and allocation of minimal production resources and lack of dissemination of the production techniques to stakeholders involved in the forage resource development. The present chapter highlights the recent advances in the forage crop production technologies. The comprehensive compilation of information at one place provides the opportunity to get the holistic picture of forage production altogether.

Introduction

The various kinds of plants present on earth have been used over the millennia for human welfare in the promotion of health and as drugs and fragrance materials. About 80% of the world’s inhabitants rely mainly on herbal medicines for their primary health care, while medicinal plants continue to play an important role in the health care systems of the remaining 20%. The use of herbal medicine and medicinal plants in most developing countries, as a normative basis for the maintenance of good health, has been widely observed (UNESCO, 1996). According to WHO (1998), herbal medicines are finished, labelled medicinal products that contain as active ingredients, above ground or underground parts of plants or other plant materials, or combinations thereof, whether in the crude state or as plant preparations. The plant materials referred to above include juices, gums, resins, fatty oils, essential oils and any other substances of this nature. Herbal medicines may contain excipients in addition to the active ingredients (WHO, 1991). Remarkably, even today there is no real definition for this special group of plants that has been accompanying mankind throughout history. Most frequently, medicinal plants are defined as feral and/or cultivated plants that, based on tradition and literature records, can be directly or indirectly used for medical purposes. The basis of medicinal use is that these plants contain so called active ingredients (active principles or biologically active principles) that affect physiological (metabolic) processes of living organisms, including human beings.

The conception about aromatic plants is even less definite. The term aromatic indicates plants having an aroma; being fragrant or sweet-smelling, while the word aroma is supposed to imply also the taste of the material (aromatic herbs). Since, large number of plants possess both medicinal and aroma properties which leads to complexity and overlapping uses of active ingredients, making impossible to establish rigid categories or a practical classification for medicinal and aromatic plants. For example; Anise, dill, coriander, thyme, etc. are equally known as medicinal, spice and essential oil crops. Thus, frequently these plants are simply referred to as medicinal plants, disregarding their specific features. More recently, the term “Medicinal and Aromatic Plants” (MAPs) has been used in a slightly broader sense, distinguishing the fragrant (aromatic, ethereal) ingredients containing group of medicinal plants.

Introduction

The general recommendation for intake of fruits and vegetables is at least 400 g/ person as recommended by World Health Organization (WHO), which amounts to five servings of 80 g/day or about 146 g/person/annum. For vegetables, the recommended intake requirement is at least 300 g per day per individual. This 300 g requirement must include 50 g leafy vegetables, 50 g roots and tubers and 200 g other vegetables (Kapur, 2016). Current annual vegetable production including potato, based on recent three years (2015-16, 2016-17, 2017-18) average is around 177 million tonnes from 10 million ha giving a productivity of 17.7 tonnes/ha. With this average and stagnating production and assuming Indian population at 133 crores (1.33 billion) and 25% post-harvest losses, per capita per day availability of vegetables comes to 273 g leaving a gap of 27 g between the recommended dose and the availability of vegetables/head/day in India. By 2050, the projected population of India is 1.5 billion and to meet the requirement of this population, vegetable production will have be 220 million tonnes, of course making allowance of 25% post-harvest losses. Considering all kind of constraints on the available land area of vegetables, the vegetable area will be around 10 million ha and consequently, major gain of production will have to come from productivity increase from current level of about 18 to 22 tonnes/ha and this seems to be a gigantic task as during last several years, the productivity of vegetables in India has been between 17 and 18 tonnes/ha, an indication that perhaps productivity has reached to a plateau. This situation will call fall massive interventions on technological fronts in terms of innovative products with focus on better hybrids with higher yields, and resistance to biotic and abiotic stresses coupled with horizontal scaling up of modern production technologies. This chapter looks into the modern production technologies as applicable to vegetable crops in India to boost the productivity further from current 18 tonnes/ha to at least 22 tonnes/ha.

Introduction

Sugarcane is a vital commercial crop of our country that occupies around 5.11 million ha of land with an annual cane production of around 400.16 million tonnes and yield of 78.25 t/ha. Sugarcane occupies 2.67% of the cultivated land area and about 7.5% to the agricultural production in the country (DAC, 2020). This crop is a source of earning and livelihood for about 35 million farmers and approximately equal number of labourers. After textile industry, the sugar industry holds its place for the largest agro-based industry in country. Around 40-50% of the cane is utilised in 435 sugar industries present in India for the manufacture of about 15 million tonnes of sugar.

This crop is also a source of raw material for two important small scale industries, i.e., gur and khandsari. These industries utilises about 50-55% of the sugarcane produced for production of about 10 million tonnes of these products altogether. Besides, sugarcane crop is also the producer of molasses, chief by product, which is the main source for production of alcohol. In the year 2018-19, about 13.79 million tonnes of molasses is produced by our country. Apart from this, the left over fibrous material of sugarcane termed as sugarcane bagasse is also a source of production of electricity in the sugar mills. The left over extra bagasse is now-a-days utilised for even production of paper in paper industries. Also, co-generation of power by this product of sugarcane as fuel is considered to be best practical thing in most of the sugar mills. Using this as a raw material, about 3500 MW power may be generated each year without the use of any extra fuel and money being less than normally utilised in case of fuel production from thermal powers. Press mud is also one of the by-products obtained from sugarcane which is considered to be rich source of organic matter and micro and macro nutrients. Even the green tops of sugarcane are being used as cattle fodder. Besides, the cool sugarcane juice full of energy is in great demands in urban area to quench the thirst of people, especially in hot summer seasons (Anonymous, 2008). The trend of sugarcane production over the years is given

Introduction

Oilseeds are the third most important group of crops after cereals and pulses in India. These are important food crops which also find their place in industrial use. Oilseeds have been an integral component of Indian agriculture since time immemorial. On the oilseeds map of the world, India occupies a prominent position, both in terms of acreage and production. India is the 4^th largest edible oil economy in the world and contributes about 10% of the world oilseeds production, 6-7% of the global production of vegetable oil, and nearly 7% of protein meal. The oilseeds production statistics of the world for the year 2016-17 includes a production of 549.98 million tonnes from an area of 234.57 million ha with the productivity of 2.34 tonnes/ha. The top countries include U.S.A., China and India with U.S.A. ranking first in all area, production and productivity of 39.25 million ha, 126.94 million tonnes and 3.23 tonnes/ha, respectively. Next is China which ranks 2^nd in production and productivity but 3^rd in terms of area; the area, production and productivity being 22.72 million ha, 54.92 million tonnes and 2.42 tonnes/ha, respectively. India ranks 2^nd in terms of area, i.e. 33.83 million ha but 3^rd in both production and productivity being 36.32 million metric tonnes and 1.07 tonnes/ha respectively.

Introduction

Pulses are the second most important group of crops after cereals in India. They are important food crops for nutritional security, soil health and sustainable agriculture. Consequently, they remained an internal component of Indian agriculture especially under rainfed since time immemorial. They are among the ancient food crops with evidence of their cultivation for over 8,000 years. India, China, Brazil, Canada, Myanmar and Australia are the major pulse producing countries with relative share of 25%, 10%, 5%, 5% and 4%, respectively. In 2017, the global pulses production was 95.98 million tonnes from an area of 95.17 million ha with an average yield of 1008 kg/ha. Dry beans contributed 32.7% to global total pulses production followed by chickpea (15.4%), dry peas (16.89%), lentil (7.91%) and pigeonpea (7.1%). About 70% of the global pigeonpea, 60% of chickpea and 17% of lentil area falls in India (FAO STAT, 2018). India is the largest producer and consumer of pulses in the world contributing around 25-28% of the total global production.

India can be proud of growing the largest number of pulse crops (grain legumes) in the world. Over a dozen pulse crops including chickpea (Cicer arietinum), pigeonpea (Cajanus cajan), mungbean (Vigna radiata), urdbean (Vigna mungo), cowpea (V. unguiculata), lentil (Lens culinaris), lathyrus (Lathyrus sativus L.), frenchbean (Phaseolus vulgaris), horsegram (Macrotyloma uniflorum), field pea (Pisum sativum), moth bean (V. aconitifolium), etc. are grown in one or the other part of the country throughout year. The latest data (2017-18) indicate that the present production of pulses is 25.23 million tonnes from an area of 29.99 million ha with productivity of 841 kg/ha (DAC, 2019) (Fig. 1). The stagnant growth of pulse production and continuous increasing human population in the country led to decline in per capita consumption of pulses from 67 g/day/person during 1951 to 35 g/day/person during 2010 (Indian Council of Medical Research recommends 65 g/day/person).

The most important pulse crops grown are chickpea (48%), pigeonpea (15%), mungbean (7%), urdbean (7%), lentil (5%) and field pea (5%). To fulfill domestic demand of pulses in the country, India has to import 3-4 million tones of pulses every year. In order to ensure self-sufficiency, the pulse requirement in the country is projected to be about 50 million tonnes by 2050 which necessitates an annual growth rate of 4.0% (IIPR, 2013).

Introduction

Pearl millet (Pennisetum glaucum L.) is the most widely grown type of millet and it is an important staple food grain crop for millions of people in arid and semi arid regions of the world. Pearl millet is very well adapted crop to growing areas characterized by drought, low soil fertility, and high temperature. It is also performs well in soils with high salinity or low pH. Because of its tolerance to difficult growing conditions, it can be grown in areas where other cereal crops, such as wheat or maize, would not survive. Physiologically, it is a C₄ plant which imparts it potential to grow under hot and dry climatic conditions. Among cereals, it is highly responsive to fertilizers and has highest water use efficiency. Pearl millet is being grown as dual purpose crop for both grain and fodder in dry areas like Rajasthan where animal production is complimentary with crop production. Pearl millet is also a good source of important essential minerals for human health like Fe and Zn hence it is useful to alleviating malnutrition.

Introduction

Maize (Zea mays L.) is one of the most versatile promising crops having wider adaptability under diverse agro-climatic conditions. Worldwide, maize is known as “Queen of cereals” because it has the maximum genetic yield potential amongst the cereals. It is cultivated on nearly 197 million ha in about 170 countries having wider diversity of climate, soil, biodiversity and management practices that contributes 36% (1135 million tonnes) of the global grain production. The United States of America (U.S.A.) is the largest producer of maize contributes nearly 33% of the total production in the world and other important growing countries are China, Brazil, India, Argentina, Indonesia, Ukraine and Mexico (Table 1).

Introduction

Wheat is pre-eminent both in regard to its antiquity and its importance as a food of mankind in the world. In prehistoric times, it was cultivated throughout Europe and was one of the most valuable cereals of ancient Persia, Greece and Egypt. Wheat has been cultivated for several thousand years in India with the evidence of presence of wheat grains in the Mohen-Jo-Daro excavations. Till 1947, the total wheat production was only about 6 million tonnes and was not sufficient to meet the demand, leading to large scale importation of wheat. Subsequently production increased due to an increase in both total cropped and irrigated area. Wheat crop has exhibited a robust growth trend since the onset of the ‘green revolution’ in 1968. India, one of the greatest success stories of ‘green revolution’, is the second largest producer of wheat in the world after China. During 2018-19 (Fig. 1) India produced a record breaking 101.20 million tonnes of wheat from 29.62 million ha area indicating 3.42 tonnes/ha wheat yield (ICAR-IIWBR, 2019). On the other hand, India is also the second largest wheat consumer after China. Thus, wheat and its various products play an increasingly important role in managing India’s food security and India became the wheat surplus nation as against the wheat deficient nation during 1960’s. The tremendous progress in area, production and productivity of wheat to the tune of 2.9, 12.2 and 4.2 times, respectively as compared to 1950 has made India (Table 1) the member of elite group of wheat exporting countries (Workman, 2018).

Introduction

Rice is the staple food for over half the world’s population. China and India alone account for ~50% of the rice grown and consumed. Rice provides up to 50% of the dietary caloric supply for millions living in poverty in Asia and is, therefore, critical for food security. Globally, share of Asia continent in rice production is more than 90% followed by America (5.2%), Africa (3.4%) and Europe (0.6%). It is becoming an important food staple in both Latin America and Africa. Record increases in rice production have been observed since the start of the ‘Green Revolution’. However, rice remains one of the most protected food commodities in world trade. Rice is a poor source of vitamins and minerals, and losses occur during the milling process. Populations that subsist on rice are at high risk of vitamin and mineral deficiency.

The Indian population of 1.32 billion is projected to reach 1.53 billion by 2030 A.D. Goyal and Singh (2002) estimated a demand of 146 million tonnes of rice (taken as 50% of total cereals) by the year 2030. On the other end of the scale, 3^rd projection puts rice demand to be 156 million tonnes by 2030 (ICAR, 2010). To meet this, it is immensely necessary to increase the productivity levels without adversely affecting the natural resource base. Achievement of the targeted production would be an uphill task in the coming decades with the shrinking natural resource base, deteriorating soil health and soil productivity, declining input use efficiency, plateauing of yields in irrigated ecologies and lack of a major yield breakthrough in rainfed ecologies. Further, slowdown in the growth rate of cereal production and growing population pressure have emerged as formidable challenges for the future food and nutritional security in India. These challenges will be more extreme under emerging situations of natural resource degradation, high energy demands, volatile markets and risks associated with global climate change (Jat et al., 2016; Lal, 2016). Since, rice is the staple food for our country’s food security primarily depends on this wonderful crop. Globally rice is cultivated now in 167 million ha with annual production of around 769 million tonnes (499.3 million tonnes, milled rice) of rough rice and average productivity of 4.6 tonnes/ha (3.62 t/ha, milled rice) of rough rice (FAO STAT, 2017). In Asian countries, >90% of the rice is produced and consumed. The other continents in which rice is grown are Africa (7.78% of the global area), South America (6.4%) and North America (1.4%).

An electron impringing on a solid surface may be scattered once, several times, or never. When an incident electron beam bombard atoms of the sample, secondary electrons (SEs) and backscattered electrons (BSEs) emerge from the sample surface. Multiple scatterings occur if the dimension of the material is greater than approximately twice the mean free path of the electrons. This scattering may be elastic or inelastic. A pear shaped volume (interaction volume) is formed as shown in Fig. 1 and this volume of excitation increases with increase in the beam voltage (electron energy) and decreases with the increasing specimen density (ion atomic number).

X-ray diffraction (XRD) is an important experimental tool used in determining crustal structure of material system in bulk and nanoregimes. Therefore, it is important to understand the basic concepts of XRD.

Characterization Tools: Microscopy

Chemical Synthesis Methods

Several methods can be used for the production of these nanoparticles, namely: (i) top-down methods (Li et al., 2006) such as vacuum sputtering (Kuhn et al., 2002) or the decomposition of iron penta carbonyl (Fe(CO)5) in organic solvents (Karlsson et al., 2005); and (ii) bottom-up methods that promote the ‘growth’ of the nanostructures via chemical synthesis, for example through the reaction of iron(II) or iron(III) salts with sodium borohydride (Wang and Zhang, 1997). However, these methods present several limitations and problems; the top-down methods are generally expensive and require specific and costly equipment while the drawbacks of the bottom-up approaches are related to safety issues due to the toxicity of sodium borohydride, the production of flammable hydrogen gas during the process (Li et al., 2006), and the tendency to form large agglomerates, very fast and at a high extent, and therefore have a reduced reactivity and degradation efficiency.

Aim

To synthesize Zero valent (Fe) (nZVIs) iron using tea leaf extract.

Introduction

In this approach extracts of natural products (in most cases green tea leaves) with high antioxidant capacities are used. The compounds present in these extracts react with Fe (III) in solution to form nZVIs (Nadagouda et al., 2010).

Aim

Phytosynthesis of silver (Ag) nanoparticles using Cassia roxburghii aqueous leaf extract.

Introduction

The Ag nanoparticles constantly exhibit adverse effects on microbes such as inhibition and inactivation (Nasrollahi et al., 2011). The Ag nanoparticles synthesized by using various biological sources such as herbs, plants and biological organisms display excellent properties in various fields i.e., non-linear optics and intercalation materials for electrical batteries as optical receptors, catalysts in chemical reactions biolabelling and as antibacterials (Sanghi and Verma, 2009).

Aim

To synthesize gold (Au) nanoparticle using fungal mycelium.

Introduction

Biosynthesis of nanoparticles is a kind of bottom up approach where the main reaction occurring is reduction/oxidation. The fungal enzymes are usually responsible for reduction of metal compounds into their respective nanoparticles.

Aim

To synthesize phosphorus (P) nanoparticles from tricalcium phosphate using fungal mycelium.

Introduction

Green nanotechnology includes a range of processes that reduce or eliminate toxic substances to restore environment. Microorganisms like fungi and bacteria having naturally bestowed property of reducing and oxidizing nanoparticles, are used for synthesis.

Biological synthesis of Zinc Oxide (ZnO) nanoparticles

Aim

To synthesize nano ZnO particles using fungal isolates.

Introduction

The ZnO nanoparticle are effective anti-bacterial and antiodur agent. Biological synthesis of ZnO nanoparticle is a new approach for environmentally benign protocol in context to green nanotechnology, (Raliya and Tarafdar, 2013).

Polymer Clay Nanocomposites

Polymer clay nanocomposites has been used as to affect permeability of the maternal to gases and vapours. Majority of papers on nanocomposites have been focused on the use of smectitic type clays as nanoparticles. They are a group of swelling type of clay minerals including montmorilonite, nontronite, saponite, sauconite and hectorite.

A number of polymer-layered silicates (PLS) preparation methods has been reported in literature. The three most common methods to synthesize PLS nanocomposite are intercalation of suitable monomer and subsequent in situ polymerization, intercalation of polymer from solution and polymer melt intercalation.

In general, layered silicates have layer thickness on the order of 1 nm and a very high aspect ratio (e.g. 10–1000). A few weight percent of layered silicates that are properly dispersed throughout the polymer matrix thus create much higher surface area for polymer/filler interaction as compared to conventional composites. Depending on the strength of interfacial interactions between the polymer matrix and layered silicate (modified or not), three different types of PLS nanocomposites are thermodynamically achievable (Fig. 1 and 2 ) as outlined by Sinha Ray and Okamoto (2003). They are as follows:

Zerovalent (nZVI) Ionic Compounds

Although Ag⁺ contains a filled d¹⁰ shell, the structures of Ag compounds can in many instances be understood only if one assumes the existence of weak attractive Ag⁺ - Ag⁺ interactions. Similar attractive forces have been shown to be responsible for the formation of gold cluster compounds. In Ag⁺ solid state compounds the unoccupied 5s and 5p orbitals give rise to empty bands which may be partially occupied thus resulting in subvalent Ag compounds; examples are Ag₃O and Ag₂F. The compound Ag₅SiO₄ prepared from Ag and Si0₂ at 350 °C under a high pressure of oxygen, contains [Ag₆]⁴⁺ clusters (average oxidation state 2/3) and should be formulated at [Ag₆]⁴⁺ (Ag⁺)₄ (SiO₄ ^{4 -})₂.

Ag and Au forms numerous cluster compounds in which the metals are zero valent or subvalent. Examples are Ag₆ Fe₃ (CO)₁₂ {HC(PPh₂)₃} and paramagnetic cluster ions [Ag₁₃ Fe₈ (CO)₃ ²]^4-.

Introduction

Hydrogels are loosely cross-linked, highly hydrophilic, organic polymers. They can absorb and retain aqueous fluids up to 500 times of their own weight (Singh et al., 2011). In the field application, such absorbents exhibited a limited swelling capacity within the soil matrix.

Aim

To synthesize chitosan/nanosilica coating solution for fruit coating aiming at increasing shelf life.

Introduction

Application of edible coatings is promising to improve the quality and extend shelf life of fruits and vegetables (Lin et al., 2011). Chitosan, a versatile biopolymer derived from deacetylation of chitin had been widely applied in the fresh-keep field owing to its good biocompatibility, biodegradability, antibacterial activity and capacities to form film (Lin et al., 2011).

Aim

To synthesize silver (Ag) nanoparticle.

Introduction

The Ag nanoparticles easily interact with other particles and increases their antibacterial efficiency. The Ag nanoparticles can be synthesized using various methods: biological, chemical electrochemical, γ-radiation, photochemical, laser ablation etc (Udapudi et al., 2012). The most popular preparation of Ag colloids is chemical reduction of Ag salts by sodium borohydride or sodium citrate (Udapudi et al., 2012).

Aim

To synthesize iron (III) oxide (Fe₂O₃) nanoparticles

Introduction

Iron oxide nanoparticles have a number of applications in catalysis, sensors and high sensitive biomolecular magnetic resonance imaging (MRI) for medical diagnosis and therapeutics. They can be synthesize by the bottom-up approaches including the sol-gel technique.

Synthesis of Zn Oxide Nanoparticle

Aim

To synthesize Zn oxide nanoparticle

Introduction

Zinc oxide nanoparticle are effective anti-bacterial and antiodur agent. They can be synthesized by number of techniques including hydrothermal methods. Their synthesis using solvothermal process is described, (Aneesh et al., 2007).

Solid state materials can exists in various forms namely:

1. Single crystals (preferred for authentic characterization of structure and physical properties)
2. Polycrystalline powders that are agglomerates of large number of crystallites and are used for characterization when single crystal cannot be easily obtained
3. Nanocrystalline or nanostructured materials that posses large surface area
4. Thin films that can be grown in the best crystalline form for many applications
5. Amorphous systems that have no long-range translational order

History and Recent Developments

Richard P. Feynman in 1959 suggested that it should be possible to build machines small enough to manufacture objects with atomic precision. His talk “There is plenty of Room at the Bottom” is widely considered to be the foreshadowing of Nanotechnology. He delivered this talk at the annual meeting of the American Physical Society at California Institute of Technology (Caltech), In 1990, a team of IBM Physicists revealed that they could write (arrange) the letter IBM using 35 individual atoms of Xenon.

In 1992 a book entitled Nanosystems: Molecular Machinery, Manufacturing and Computation was published by Eric Drexler where he outlined a way to manufacture extremely high performance machines out of molecular carbon lattice (diamondoid).

Around year 2000, federal funding for Nanotechnology in the United States began with National Nanotechnology Initiative (NNI). NNI defined nanotechnology as dealing with materials with sizes between 1 and 100 nanometers exhibiting novel properties.

The Government of India, in May 2007 launched a mission on Nano sceince and nano technology (Nano Mission) with an allocation of `1,000 crores.

7.1 Economics and Valuation of ghgs emissions

Since the late 20^th century, it has been largely accepted that cause of high concentration of GHGs in atmosphere is induced by human activities. Greenhouse gas emissions and related climate change has opened up debate on overall economic losses and ways to reduce these loses. Moreover, apart from curbing monetary losses; the global political leaders as well as reputed economists are looking towards making money by saving the emissions. Recently, the researchers have started to emphasize on the actual value added to the ecosystem by curbing emissions, discrete of the economic benefits. This section will discuss the economics and ecosystem services related to the management of GHG emissions.

Origin

The initiative to curb the emissions started in 1992 with the United Nations Framework Convention on Climate Change (UNFCCC) at the Earth Summit in Rio de Janeiro. The Convention took place from 3 to 14 June, 1992. The UNFCCC is an international environmental treaty designed to “stabilize greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system”. The UNFCCC had non-binding limits on greenhouse gas emissions for individual countries and the framework was only meant for formulating precise international treaties (called “Protocols” or “Agreements”). It contained no execution mechanisms, however, it considered some negotiations and suggestions to formulate the action plans and regulation guidelines under UNFCCC to fulfill the objective of reduction of GHG emissions to the desired level.

What is mitigation of GHGs emission? We must be clear about the answer of this fundamental question. In simple term, the mitigation of GHGs emission is the way or means by which the emission of those gases could be reduced. As we know from the previous chapters of this book that the GHGs emission could be occurred from natural as well as anthropogenic activities. Natural activities included volcanic eruptions, ocean current fluctuations, continental drifts which are responsible for emission of huge amount of CO₂ and other GHGs. The reduction of emissions from those natural activities is beyond our capabilities. However, the human induced emissions of GHGs emission could be reduced. We studied in previous chapters that fossil fuel burning, industrial and energy sector pollution, deforestation, land use change and agricultural could contribute to GHGs emission considerably. Mitigation techniques are different for each of those sectors that governed by lot of interrelated factors. In actual sense, the mitigation of GHGs emission should includes all the measures that can curtail the anthropogenic emission from all sectors. But that is out of the scope of this book. In this book, we specifically address the mitigation principles, options and efficiency of different techniques/ practices in agriculture only.

In that aspect, the mitigation of greenhouse gases emissions in agriculture is defined as “the means and ways by which emissions of GHGs could be reduced from agriculture”. The ways and means actually referred to the techniques and practices and their amalgamation in agricultural sector both in production, processing and consumption aspects. So, mitigation is not only a techniques or combination of techniques it is actually an integrated approach for reducing greenhouse gases emission from agricultural systems. Primarily, there are two complementary approaches for mitigation of GHGs emissions from agriculture. Those two approaches are (i) supply-side and (ii) demand- side options or pathways. The supply-side approaches includes scientific land- use-changes, improvement of crop management, better livestock management practices, enhancing carbon storage in biota, soil carbon sequestration, significant substitution of fossil fuel by bio-fuels and use of renewable energy in agriculture. On the other hand, demand side approaches, taken in to account of shifting in the dietary pattern from non-vegetarian to vegetarian, curtail down the food loss and waste, and reducing the supply-chains (Figure 6.1). We can see, most of the approaches in supply-side are technology driven, while, approaches in demand-side are socio-economical and or policy driven. In this chapter we would thoroughly discuss the principles of mitigation, options of mitigation, mitigation cum adaptation approaches to reduce GHGs emission and climate change and few strategies to cope up with the vagaries of climate change.

5.1 Impact of climate change on agriculture

Climate change has both positive and negatively impact on agriculture, food security and land degradation. Climate change could exacerbate the land degradation processes by increases in rainfall intensity, drought frequency and severity, dry spells, f looding, heat stress, sea-level rise and permafrost thaw. The 1/4^th of ice-free land area in the world is prone to human-induced anthropogenic degradation (Certini and Scalenghe, 2011; Hooke et al., 2012). Soil erosion rate is 20-100 times faster than that of soil formation in agricultural field. The erosion rate is least is zero-tillage (non-disturbed field) and maximum at conventional intensive tillage practices. Climate change further exacerbates the land degradation. The permafrost areas, dry-lands, low-lying coastal regions, river deltas are more vulnerable. The occurrence of drought in dry-land was increased by around 1% per year during 1961-2013 periods. On an average 380-620 million people globally experienced desertification who lived in dry-land areas (1980s and 2000s) in South and East Asia, North Africa, Middle East, Sahara region, and Arabian peninsula. Moreover, people who are already living in degraded/ desertified regions are more negatively affected by climate change.

Specifically, the land surface air temperature has increased about twice as much as the global average temperature since the pre-industrial era. The land-surface air temperature has increased relatively higher than the world’s average surface (land and ocean) temperature since the pre-industrial era (1850-1900). The average land-surface air temperature has enhanced by 1.53°C (1.38-1.68°C), whereas, world’s surface (including land and ocean) air temperature has enhanced by 0.87°C (0.75-0.99°C). Subsequently, global warming triggered the frequency, intensity and duration of heat waves and related damage. The direct and indirect impacts of climate change on global agriculture is summarised below for an overall idea about the importance of the issues.

The measurement of greenhouse gases (GHGs) has been started during middle of the last century. Initially, CO₂ and water vapour were measured with other common meteorological variables like temperature, sunshine hours, rainfall, humidity etc., for monitoring the weather condition and pollution. The absolute or relative concentrations of gasses in atmosphere are used to measure basically for monitoring purpose. However, limited studies were dealt with actual gaseous exchanges of fluxes. The concern about gaseous flux measurement and GHGs-exchanges started after 1900s when people got concerned about anthropogenic pollution, environmental sustainability and climate change issues. The GHGs-exchanges in earth-atmosphere systems primarily occur due to change in meteorological variables, soil responses and physiological activities of crops. If we are interested for environmental data inventories, then absolute GHGs concentrations of atmosphere at a specific time is required. However, presently researchers, students, environmentalists, climate scientists are primarily interested for quantitative data on GHGs fluxes and or GHGs-exchanges. They want to know what and how much quantity of a particular GHG is emitting from unit area at unit time.

Flux refers to the amount of any gas emitted per unit area per unit time. The dimension of that is M A^-11 T^-1. (Where, M= Mass/ Quantity; A= Area; T= Time). The SI unit of flux is g m²s^-1. Therefore, flux is a vector. It has magnitude as well as direction. As for example positive flux of CO₂ from earth surface means, CO₂ is moving out from earth surface to atmosphere. If it moves in opposite direction then the flux would be negative. In that case CO₂ gas may be absorbed by the soil surface from adjacent atmosphere. Similarly, GHGs fluxes of earth surface are either positive or negative. Generally, positive GHGs flux refers to emission of GHGs from earth to atmosphere and vice versa.

3.1 Chemistry of greenhouse gases (ghgs)

Greenhouse gases (GHGs) are atmospheric-gases that have capabilities to absorb and radiate-back the infrared (IR) radiation in the earth-atmosphere system (Figure 3.1). In this process the atmospheric-gases absorb and radiate- back IR radiation in lower atmosphere effectively emitting and absorbing heat energy heat energy. They maintain the heat budget of earth-atmosphere and keep our plant warm. If we typically see the chemistry of those gases, the key point is that they should have dipole moments. This is the property which makes them capable to absorb and radiate-back the range of IR radiation. In a molecule when valence-electrons are not equally shared in a bond between the two atoms, a slight positive charge is developed above one atom and a negative charge on the other atom. That charge difference of the different atoms in a molecule generates the dipole moment. For instance, in water vapour (H₂O- vapour), an unequal sharing of electrons and or separation of charge causes dipole moment. In H₂O, the centre has a positive charge at the hydrogen atoms and negative charges are located on the oxygen atom. The magnitude of dipole- charges, vibration and stretching of O-H bond generates certain frequency of the oscillating dipole moment that actually regulates the absorption capacity of IR radiation by H₂O vapour.

Climate change is caused by both natural as well as anthropogenic causes and it has been changing since the inception of earth-atmosphere (Figure 2.1). In a broader sense, anthropogenic activities (human activities) also must be considered as natural one in longer time scale as human and their activities are also a part of natural-ecosystem-functions. Among the natural phenomena, volcanic eruptions and continental drifts significantly affect the earth’s precipitation and temperature. A huge volume of CO₂ is released due to volcanic eruption at a little span of time-period which heated up the earth-atmosphere. Climate variability is primarily governed by rise in sea temperature, movement of warm water from the Western Pacific towards Peru, and El Nino which occurs at an intervals of 3-7 years. Climate variability also influenced the alteration in temperature and precipitation world wide. And persistent climate variability cause long term climate change. Therefore, basically three drivers that causes climate change are, the alteration in the energy of sun received by earth-atmosphere (natural causes), variations of ref lectivity of earth-surface- atmosphere system (natural as well as anthropogenic causes) and fluctuations in the greenhouse effect (natural as well as anthropogenic causes).

1.1 Weather

Firstly, what is weather? Simply, the conditions in the atmosphere above the earth is called weather. It refers to the conditions such as wind, rain and temperature, prevailing at a particular location during periods of hours or days. We often ask “what’s the weather like today”? Any individual can answer to this question as it requires only a short term experience or say exposure to the atmosphere. The TV news forecasters predict weather each day and inform about the temperature, cloudiness, humidity, or possibility of storm in the next few days. Weather is localised, say, it’s a hot and cloudy weather in one part of the country and dry and windy on the other part.

1.1.1 What are the factors that influence weather?

Before we try to understand the factors that influence weather, we must understand what the components that describe a weather conditions are? Is it the rains, or the air temperature or both? The answer to this question is not so easy, and it’s a bit complicated. There are many components that constitute weather. Weather components include rain, cloud cover, sunshine, winds, hail, snow, sleet, storms, thunderstorms, heat waves and many more. These components are sometimes referred as weather parameters or climate elements. Each of these components define weather patterns of a particular area. These components determine the status of local atmospheric conditions. Again, as a basic definition, weather is the state of the atmosphere and majority of weather phenomena occur in the lowest layer of the atmosphere, called as the troposphere. Does it mean that ground conditions such as the topography, water bodies and vegetation of a particular area has nothing to do with it? No, it is not so. The state of the atmosphere is subjected to various processes taking place not only in the atmosphere but also in the ocean, the sea-ice, the vegetation, etc. Weather parameters or the components of weather form a sequence of events, and the influences are far reaching and they do not remain solely in the atmosphere. For example, terrestrial radiation impacts the air temperature, air pressure and humidity. The terrestrial location also influences the cloud formation. The clouds may or may not turn into precipitation depending on the outcome (cloud or rain), which is by and large governed by troposphere. Likewise, a lack of precipitation affects not only weather conditions, but also soil moisture conditions that may result in lowering of water levels (ground water table) in soil. Wind speed and direction are governed by the atmospheric pressure and air temperature. So, all these parameters or components are interrelated and the weather conditions are the outcome of their interactions. Therefore, we can say that, the three main components of weather are temperature, precipitation and solar radiation. These components are influenced by different factors.

In this Chapter the precision farming/ Agriculture is discussed along with its steps of implementation. It also includes how artificial Intelligence plays role to perform precision farming/ agriculture in various way along with its scope, limitation and challenges.

Introduction

The primary source of livelihood is agriculture in India, where two thirds of India’s population, services and the private sector account for the remainder. Agricultural land accounts for about 43 percent of the geographical area of India. In earlier days, India was largely dependent in terms of food imports, but over the years, the country’s production of grain and seeds was self-sufficient, and this effort led to the formation of the Green Revolution. In fact, there was strong effort to achieve food self-sufficiency. This trend has continued up to now and continuous improvements have occurred. Precision agriculture or precision farming means the right thing to do, in the right way, on the right place and at the right time. Precision agriculture is expected to suit the agro-climate activities to improve application precision. Farming land has declined a bit in the last 40 years but the number of farmers has increased. According to the 2010–11 Agriculture Census, a total of 138.35 million operating holdings were estimated (single farmers) and 159,59 million hectares were covered by operations.

Precision agriculture is a management technique that collects, processes and analyzes temporary, spatial and individual data and integrates this with other information in order to support management decisions based on an estimated variability to enhance efficiency of use of agricultural production resources, productivity, quality, profitability and sustainability. Precision Agriculture manages every input of crop production (fertilizer, specifically found calestone, herbicide, seeds, insecticide, etc. Reduce waste, boost income and maintain efficiency Place. Precision Agriculture adapts soil and crop management carefully to suit the different field conditions.

Introduction

The conventional approach of the human person for plant classification is comparing the color and shape of the leaves, but by using Artificial Intelligence analysis can provide quicker and more detailed results by analyzing the morphology of the leaves and provides more details about the leaf properties. Species Recognition has been a very important part of agriculture and there are thousands of species in plants which can be identified by a single person and even if it does so It will take a huge lot of time to do it.

In this chapter we will discuss and built a project related to identify species in flower with an image. In this project we will be using Artificial Intelligence different branches like machine learning, deep learning and computer vision to build such an amazing project. So, let’s begin

Introduction

In agriculture, plant diseases have always been a major problem, as they cause crop quality to decrease, resulting in yield. Plant disease has a range of effects from minor symptoms to serious damages in whole crop areas, which lead to high financial costs and significantly impact the agricultural economy, particularly in developing countries dependent on a single crop or on a few crops.

Various approaches have been developed to detect disease in order to avoid significant losses. Causal agents have been precisely defined by methods developed in molecular biology and immunology. However, for many farmers these techniques are inaccessible and require detailed knowledge of the field or substantial time and energy to be used. According to the United Nations Food and Agriculture Organization, most farms in the world are small and family-owned in developed countries. Such families provide food for a significant proportion of the population of the planet. However, hunger and food insecurity are not rare and there is restricted access to markets and services. For the above reasons, a great deal of work has been undertaken in order to establish methods that are sufficiently reliable and available to most farmers. Where Plant disease is an essential factor contributing to a major decline in plant production quality and quantity. Plant disease identification and classification are a significant role in improving plant production and economic development.

In this chapter of machine learning algorithms we will cover the basic algorithms of machine learning with their implementation using dataset and discuss their pro’s and cons of algorithms for better understanding and how to use them in any project or with any dataset to get an correct result which can useful for research or study.

Key Component

We defined a data set composed of audio, images and binary labels that provided an understanding of how we could train a model from snippets to classifications. This sort of problem is one of many kinds of machine learning problems when we try and predict a specified unknown label given known inputs, provided that a dataset of examples for which labels are known is called supervised learning. Let’s discus what are the major key components we have to get there

In this chapter we will cover all the basics libraries and some frameworks of machine learning, deep learning and computer vision. We will discuss all about their use with an example and instruction which will states the commands to install to those libraries for building any project in our system. So let’s begin

What is a Library?

Library is an aggregate of features and methods that allow you to take many actions without getting your own code written.

For instance, the libraries that you have to know are if you work with data, numpy, scipy, pandas, etc. They have very simple data processing functions that save you time for small tricks.

In this chapter we will talk about the tools which are required to make project in artificial intelligence. All this bellow discussed tools are uses python programming language for making any project in any respective field. We have discussed about how anyone can install and use the tools to built a real time project in artificial Intelligence.

Using Python IDE

To download and install Python visit the official website of Python https://www.python.org/downloads/and choose your version. We have chosen Python version as per requirement all the codes in this book were on python version 3.6 as you can see in the Fig. 7.1.

In this chapter we will look at the Expert system which can guide and assist an individual once it is provided with the enough Knowledge to do so. Here we will discuss about expert system and its architecture with proper steps of making an expert system in any field by several tools which are available to do so. For expert systems the most important is Knowledge Engineering which is the collection of Knowledge from an expert and Engineering it in such a form that a machine could understand it.

Introduction

One of the pioneering fields of AI study is Expert Systems (ES). It is proposed by researchers in the computer science department of Stanford University. An expert system is a computer system which emulates a human expert’s decision-making skills. Expert systems are developed by reasoning through information structures, representing laws, rather than through traditional procedural code, in order to overcome complex problems.

Expert Programs use professional expertise systematically to address human expert problems. An expert is an individual with experience in a specific field. The expert has expertise or special credentials which most people do not learn or care about. An expert can solve or solve problems more effectively than people can solve. Expert System actually emulates all these qualities of expert and solve the problem in a better way and fast.

Today, Expert System (ES) is used in the fields of finance, research, engineering, technology, medicine and many others where there is a well-defined problem area. The fundamental principle is that an expert method should also define the steps to illustrate why a problem can be solved. Unless an individual can justify his reasoning for Expert System.

Introduction

Agriculture has played an important role in the global economy in recent years. The further growth of the population is leading to a gradual decrease in the area of the agricultural land and further growing stresses on the farm system. Agricultural food production methods are rising in demand for successful and healthy. Innovative sensoring and motive technologies and advanced information and communications systems and Artificial Intelligence must supplement conventional agricultural management methods to speed up farm productivity growth more accurately, thereby promoting the production of high-quality and high-performance agriculture. Computer vision monitoring systems have become valuable tools in farm operations over the past decades, and their use has increased significantly.

What is Computer Vision?

Computer vision can be characterized as a field of AI for extracting information from digital images. The type of data obtained from an image may be different from recognition, navigational space measurements or applications of increased reality.

The applications of computer vision can also be described. Computer vision builds algorithms that recognize and use the quality of pictures for other purposes.

Deep learning emerged as a serious contender in the field from a 10-year explosive computational development. Deep learning is therefore a special form of machine learning, the algorithms of which are based on the structure and function of the human brain.

Machine learning VS Deep learning

Deep learning is arguably the most efficient form of machine learning. This is so important because they know the best way to solve the problem and how to fix everything. The following is a description of deep learning and machine Learning: