eChapters

As we have seen how artificial Intelligence can be useful in agriculture but the nest question always come in mind is that from where and how we can start to learn and what are the model of learning an artificial Intelligence. As Artificial Intelligence is a huge part of Computer Science which means we need an language as medium to perform it and we always prefer Python for that which is very dynamic and easy to learn. In this chapter we will learn about python basics so that in further implementation of artificial Intelligence it will be helpful to us.

I. Introduction

Python is a remarkable language that can claim to be easy and strong. You will be amazed to see how simple it is not to focus on the language you are programming, but on solving the problem. Guido van Rossum was the creator of the Python language which is named after the BBC show “Monty Python’s flying Circus”.

Python is formally introduced as:

“Python is an easy to learn, powerful programming language. It has efficient high-level data structures and a simple but effective approach to object-oriented programming. Python’s elegant syntax and dynamic typing, together with its interpreted nature, make it an ideal language for scripting and rapid application development in many areas on most platforms.”

As we know there are different branches of artificial Intelligence and machine Learning of one of them which has become a most advance and widely used branch of artificial Intelligence in every field of this generation whether it may be either electronics, civil, mechanics, Bioengineering, medical or agriculture etc., In this chapter we will study about machine learning and its types with the most common algorithms of machine learning which are being mostly used in different scenarios and their implementation using python language has been discussed in the implementation part of this book. Here we will also see where machine learning can be used.

i. Introduction

Machine learning is a subset of Artificial Intelligence and one of the most important part of artificial Intelligence. It is a field of Computer science which is totally differs from traditional computational approaches. In traditional approaches, a set of instruction is explicitly provided to the algorithm to solve any problem. Whereas in Machine Learning is a domain of an AI which uses a statistical analysis and can enables a system to always learn from its data without any external inputs in order to give an essential output. Due to this machine learning makes computers in advance to make model which provide decision based on input data.

Machine Learning involves a lot of algorithms which usually based on their requirements and functionalities to use where and when. To make a machine learning model we always require the data on which model can be made. Machine learning uses the algorithm which continuously learns from the data available as training data. A machine learning model is generated after the training of algorithm from the data. After the training completes, when trained model is provided with other real-life data then you can get an essential outcome. For example, in figure 3.1 Machine learning Model we use a predictive algorithm and make a model by providing it with some data, and later on we can receive prediction’s based on real data as input.

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:

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.

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.

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 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 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

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.

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

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

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%).

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Climate change and agriculture are interrelated issues, both of which take place on a global scale. Global warming is projected to have significant impacts on conditions affecting agriculture, including fluctuation of temperature, carbon dioxide, glacial run-off, precipitation and the interaction of these factors (Sehgal et al., 2006; Kalra et al., 2008). These conditions determine the carrying capacity of the biosphere to produce enough food for the human population and for domesticated animals. The overall effect of climate change on agriculture will depend on the balance of these effects. Assessment of the effects of global climate changes on agriculture might help to properly anticipate and adapt farming to maximize agricultural production. Droughts, which have frequented different parts of India through the history, have been responsible for many famines, rural poverty and migration despite development of impressive irrigation potentials. Similarly, abnormal temperatures, high velocity winds and humidity during critical stages are known to significantly affect crop growth and development, pest incidences and epidemics, demand on irrigation resources and finally food production. Over the past few decades, the main-induced changes in the climate of the earth due to multifarious human activities linked to develop have become the focus of scientific and social attention. The predicted changes to agriculture vary greatly by region and crop. Findings for wheat and rice are reported here: The study found that increase in temperature (by about 2 ºC) reduces potential grain yield in most places. Regions with higher potential productivity (such as northern India) were relatively less impacted by climate change than areas with lower potential productivity (the reduction in yields was much smaller). Climate change is also predicted to lead to boundary changes in areas suitable for growing certain crops. (Kalra et al., 2002-2003). Reduction in yields as a result of climate change is predicted to be more pronounced for rainfed crops (as opposed to irrigated crops) and under limited water supply situations because there are no coping mechanisms for rainfall variability. The difference in yield is influenced by baseline climate. In sub-tropical environments, the decrease in potential wheat yield ranged from 1.5 to 5.8%, while in tropical areas the decrease was relatively higher, suggesting that warmer regions can expect greater crop losses.

Introduction

Any computer that has Microsoft office excel in it can operate this statistical calculator. Operating system requirement is Windows 7 or its higher version. Usually looking at a data we become nervous and start thinking that how to analyse the data using computer programme, how to write the report of the research analysis etc. This newly developed statistical calculator will remove the fear of data analysis and make our life easy. This calculator will get the data analysis done within a very reasonable computing time.

This chapter introduces a new statistical calculator which provides a step-by-step guide to data analysis of the research data generated in agriculture, biological sciences and in other fields (Singh and Chaudhary, 1985; Chandel, 1998; Bhattacharya and Chowdhury, 2010). The process used to develop the program is quite involved with statistical theories and is not understandable to those who do not have any background in statistics and data analysis. Here we will explain the procedure adopted and the programme used, step-by-step so that it becomes easily comprehensible. We have provided examples in each spreadsheet for analysis. Data analysis with this statistical programme is not really difficult. According to the draft format required for analysis, you only need to arrange and enter the raw data. It does not require much information and knowledge about the formula used as well as the program developed to analyze the data (http://www.sbear.in/).

Abiotic stress: Unfavourable situation created by non-living factors to the growth and development of plants. Factors include water, temperature, soluble salts, heavy metals, etc.

Abscissic acid (ABA): A plant hormone belongs to isoprenoid compounds. It is also known as stress hormone since it has relevance in stress tolerance in plants. Some of the physiological effects of ABA are closing of stomata, synthesis of osmolytes and seed dormancy.

Abscission layer: Distinct layer of cells with weakened cell walls in abscission zone.

Abscission zone: A region near the base of petiole of leaf which contain abscission layer.

Bacteriochlorophylls: A group of light absorbing photosynthetic green pigments of anoxygenic photosynthetic bacteria.

Ballistic transformation: The use of a particle gun to insert foreign DNA into a host.

Beneficial elements: These are the elements that help to optimize the growth and development only in some species. It is not essential to all the plants. Aluminum is beneficial to some species that are adapted to acidic soils. Cobalt can have a number of beneficial effects, especially in leguminous plants.

Betalains: Highly coloured nitrogen containing glycosylated compound in the category of alkaloids imparting red-purple and yellow colour in plants of centropsermae (e.g., beet root).

Beta-oxidation: Breakdown of fatty acids into Acetyl co-A by successive oxidation. It is the first step of lipids breakdown.

Bidirectional transport: Simultaneous transport of solutes in opposite directions in the same file of sieve elements. Bidirectional transport may occur under some circumstances. For e.g., in a file of cell, as a result of cytoplasmic streaming.

C₃ cycle or Calvin cycle: It is a process of dark reaction of photosynthesis. It is also called as photosynthetic carbon reduction cycle which results in the production of sugars. It occurs not only in C₃ plants but also in C₄ and CAM pathway also. It occurs in the mesophyll cells. It is described in three stages: (1) Carboxylation, (2) Reduction, (3) Regeneration.

C₃ plants: Group of plants with calvin cycle wherein the first stable product is 3-phosphoglyceric acid, a three carbon compound. e.g., rice, wheat, barley.

C₄ cycle: C₄ cycle may also referred to as the dicarboxylic acid cycle or Hatch and Slack Cycle. The first stable product is a C₄ compounds like oxaloacetic acid. Here CO₂ molecule is accepted by phosphoenol pyruvate in the carboxylation reaction. The main purpose of this cycle is carbondioxide enrichment.

C₄ plants: Plants with Hatch-slack pathway and kranz anatomy of leaves in which the first stable product is four carbon compound, oxaloacetic acid. These plants posses high photosynthetic efficiency and low photorespiration rate. e.g., sugarcane, maize, sorghum.

Dark reactions: It is light independent reactions occurs during daytime. This includes C₃, C₄ and CAM pathway involving the utilization of NADPH and ATP to fix CO₂ into carbohydrates. It is also called as stromal reactions.

Day neutral plants: The plants that flowers regardless of the length of the period of the light that is exposed to. They are called as day neutral plants.

DCMU (Dichlorophenyl dimethyl urea or diuron): An herbicide that inhibits non-cyclic photophosophorylation specifically blocks the electron flow at the quinone acceptors of PSII, by competing for the binding site of plastoquinone that is normally occupied by PQB.

DCPIP (Dichlorophenol indophenols): A dye often used as artificial hydrogen acceptor to demonstrate in Hills reaction in isolated chloroplast in laboratory. The oxidized form is blue in alkali and red in acid, while reduced form is colourless.

Ectodormancy: A kind of dormancy which is due to environmental factors.

EDTA: An important chelating agent often used in modern nutrient solutions. It forms soluble complexes with metal ions such as that of iron and prevents from precipitation in the solution.

Elaiosomes: Greek élaion means “oil” and sóma means “body” , are fleshy structures that are attached to the seeds of many plant species. The elaiosome is rich in lipids and proteins, and may be variously shaped. Many plants have elaiosomes that attract ants, which take the seed to their nest and feed the elaiosome to their larvae and by which the seed get dispersed.

Electrical conductivity: Electrical conductivity is the measure of a material’s ability to allow the transport of an electric charge. It is used to measure the level of salinity in water or soil. When electrical conductivity is more, then salinity is more since as salt concentration is more in water or soil, then those salts will conduct more of electricity. Normally measured in μS/cm.

Electrical impedance: The application of alternating electrical current to pre-frozen or frozen plant tissues to predict damage or measure injury, respectively.

Facilitated diffusion: Facilitated diffusion is a movement in the direction of a concentration gradient; but it involves moving through a channel protein or a carrier protein. A channel protein is merely a pore in the membrane, and is often gated to control movement. A carrier protein has a binding site where the substance attaches and moved through the membrane.

Facultative CAM: Plants which behave as C₃ under conditions of normal water supply. However, switch over to CAM mode under conditions of water deficit.

FAD (Flavin adenine dinucleotide): A riboflavin containing co-enzyme of some oxidation reduction reactions.

Facultative long day plant: Facultative photoperiodic plants are more likely to flower under appropriate light conditions, but will eventually flower regardless of length of night.

FADH: In biochemistry, flavin adenine dinucleotide (FAD) is a redox cofactor, more specifically a prosthetic group, involved in several important reactions in metabolism. FAD can exist in three different redox states, which are quinone, semiquinone and hydroquinone. FAD is converted between these states by accepting or donating electrons. FAD, in its full oxidised form or quinone form, accepts two electrons and two protons to become FADH₂ (hydroquinone form). The semiquinone (FADH) can be formed by either reduction of FAD or oxidation of FADH₂ by accepting or donating one electron and one proton, respectively.

Gel: A semi-solid medium in to which proteins or nucleic acids are subjected to electrophoresis, to determine their size or to separate them from other components.

Gene family: A set of genes whose sequences differ only slightly that encode identical products; within a single species, a multigene family.

Gene tagging: The addition of a marker to a gene; often by the introduction of a transposon or insertion element.

Gene transfer: Transformation; the insertion of foreign DNA into a host conferring a trait not previously inherant in that organism.

Gene: The concise meaning might be the sequence of DNA that encodes a gene product (an RNA or protein), including all upstream and downstream sequences involved in the expression of the gene.

Genome: Sum of all genetic information of an organism, nucleus, organelle, or virus.

Geotropism (Barytropism or gravitropism): When a seedling is kept horizontally on the soil, the radicle always grows towards soil, and the plumule grows away from the soil. This type of growth movement of radicle and plumule is called positively geotropic and negatively geotropic respectively. But some runners and rhizomes grow parallel to the surface of the soil and this is referred to as diagiotropic. When the lateral roots grow obliquely into the soil, it is referred to as plagiogeotropic phenomenon.

Germination percentage: Germination percentage is an estimate of the viability of a population of seeds.

Half life: The time required for the disappearance of one half of a given component of a system.

Halochromism: It occurs when a substance changes color as the pH changes. This is a property of pH indicators, whose molecular structure changes upon certain changes in the surrounding pH. This change in structure affects a chromophore in the pH indicator molecule.

Halomorphic soil : A suborder of the intrazonal soil order, consisting of saline and sodic soils formed under imperfect drainage in arid regions and including the great soil groups Solonchak or Saline soils, Solonetz soils, and Soloth soils.

Hatch-Slack pathway: It is one of the carbon fixation pathway used by certain group of plants (C₄ plants) where the first stable compound is oxalo acetate, a C₄ dicarboxylic acid compound. In the first carboxylation reactions, atmospheric CO₂ combines with phosphoenol pyruvate (PEP) to oxalo acetate and then to malate. These plants posses kranz anatomy with mesophyll and bundle sheath cells.

Ice nucleation: It is a process of reducing the formation of ice crystal under freezing stress, by some polysaccharides and proteins known as ice nucleators.

Imbibitions: It is a special type of diffusion when water is absorbed by solids-colloids-causing them to enormously increase in volume. The classical examples of imbibition are absorption of water by seeds and dry wood.

Immobile elements: The elements which get translocated slower inside the plant are called immobile elements. Examples: Ca, Fe and B.

Immunoassay: This is very sensitive method of identifying and or quantifying the hormones and other molecules which has antigen and antibody interaction.

Indeterminate growth: Plant growth in which the main stem continues to elongate indefinitely without being limited by a terminal inflorescence or other reproductive structure; also growth is characterized by sequential flowering from the lateral or basal buds to the central or uppermost buds.

Indole -3 acetic acid: It is naturally occurring auxin responsible for cell elongation, apical dominance and other physiological functions of auxins.

Induced dormancy: Induced dormancy in which dormancy develops as a response to external environmental factors.

Jasmonic acid: Jasmonic acid is derived from the fatty acid, linolenic acid. It is a member of the jasmonate class of plant hormones. It is biosynthesized from linolenic acid by the octadecanoid pathway. The major function of JA and its various metabolites is regulating plant responses to abiotic and biotic stresses as a well as plant growth and development processes.

Ketose: A simple sugar in which carbonyl group is a ketone.

Kinases: Enzymes that catalyse phosphorylation of an acceptor molecule such as protein molecule by ATP.

Lactate dehydrogenase: An enzyme that reversibly catalyses conversion of pyruvate to lactate by utilizing NAD as coenzyme. This operates under anaerobic respiratory condition.

Lactate fermentation: Lactic acid fermentation is a biological process by which glucose and six carbon sugars (also, disaccharides of six carbon sugars, e.g. sucrose or lactose) are converted into cellular energy and the metabolite lactate. It is an anaerobic fermentation reaction.

Latent heat: The heat required to convert a solid into a liquid or vapour, or a liquid into a vapour, without change of temperature. It is also called as hidden heat.

Leaching requirement: (LR) The amount of water in excess of the plant requirement that is needed to remove salt from the root zone in order to prevent soil salinity from exceeding a specified value.

Leaf Area Duration (LAD): It is the functional leaf area or estimated photosynthetic area which contributed for the total biomasss. To correlate dry matter yield with Leaf area, Power et al., (1967) integrated the Leaf area with time and called as Leaf Area Duration. LAD taken into account, both the duration and extent of photosynthetic tissue of the crop canopy. The LAD is expressed in m². days.

Macromolecule: A molecule having molecular weight ranging from few thousand to millions.

Macronutrients: The essential elements which are required by plants in comparatively large amounts are called as major elements or macro nutrients. Examples: C, H, O, N, P, K, Ca, S, Mg. In this C, H, O, N, P, K are called primary elements and Ca, S, Mg are called as secondary elements.

Malate shuttle: A mechanism of transferring reducing equivalent of cytosolic NADH in the form of malate across the inner mitochondrial membrane by a specific ketoglutarate malate transporter for oxidation through electron transport chain in little animal tissue like heart muscle.

Malic enzyme: An enzyme that catalyzes the oxidation of malate to pyruvate and carbondioxide.

NAD/NADP (Nicotinamide Adenine Dinucleotide/ Nicotinamide Adenine Dinucleotide Phosphate): Coenzymes acting as carriers of hydrogen atoms and electrons in some oxidoreductases catalyzed reactions. Their oxidized and reduced states are NAD⁺ and NADH + H⁺/NADP⁺ and NADPH + H⁺

Nanotechnology: Nanotechnology refers broadly to a field of applied science and technology whose unifying theme is the control of matter on the molecular level in scales smaller than 1 micrometre, normally 1 to 100 nanometers, and the fabrication of devices within that size range.

Nastic movement: Nastic movements are non-directional responses to stimuli (e.g., temperature, humidity, light irradiance), and are usually associated with plants. The movement can be due to changes in turgor or changes in growth. An example of such a response is opening and closing of flowers. There are several types of nastic movements such as Epinasty, Hyponasty, Photonasty, Nyctinasty, Chemonasty, Hydronasty, Thermonasty, Geonasty/Gravinasty, Thigmonasty, etc.

Obligate photoperiodism: Obligate photoperiod plants absolutely require a long or short day before flowering. If required photoperiod condition is not met they won’t flower. This phenomenon is called obligate photoperiodism.

Oleosome (Spherosome or oil body): Cell organelle bounded by a single membrane and contains triglycerides.

Oligohalophyte: A plant adapted to habitats of low salinity (0.04 to 0.4 MPa at field capacity; EC 1 to 10 dS/m).

Oligomycin: An antibiotic that inhibits oxidative phosphorylation by blocking the activity of F₀F₁ ATP synthase.

Oligosaccharide: A molecule containing fewer number of monosaccharide units joined by glycosidic bonds.

P680: Reaction center chlorophyll in Photosystem II (PSII) which absorbs maximum light of 680 nm in its neutral state.

P700: Reaction center chlorophyll in Photosystem I (PSI) which absorbs maximum light of 700 nm in its neutral state.

P870: Form of bacteriochlorophyll in reaction center of pigment system in photosynthetic purple bacteria that absorbs light maximally at 870 nm in its neutral state.

Paclobutrazol: It is a chemical compound which inhibits Gibberellin biosynthesis. It is also a growth retardant commercially used in overcoming alternate bearing of mango.

Palindrome: Inverted repeats of DNA such that the sequence is the same when read forward or backward; e.g., CAGTTGAC, or in the English language, “Madam, I’m Adam.”

Palisade Parenchyma : Palisade parenchyma cells are seen beneath the upper epidermis. It consists of vertically elongated cylindrical cells in one or more layers. These cells are compactly arranged without intercellular spaces. Palisade parenchyma cells contain more chloroplasts than the spongy parenchyma cells. The function of palisade parenchyma is photosynthesis.

Pantothenic acid (Vitamin B₅): An important constituent of coenzyme A which is involved in transacylation reactions.

Q₁₀ (Temperature coefficient): The ratio of the rate of chemical reaction at a particular temperature to the rate of that chemical reaction exactly at 10°C lower.

Qualitative photoperiod: Qualitative plants are those in which a particular photoperiod is an absolute requirement for the occurrence of a response. Ex: Common cocklebur

Qualitative response (absolute response, obligatory response): A plant response, usually flowering, that absolutely depends on some day length, temperature, or other environmental stimulus. If the plant does not experience the required stimulus, the response does not occur (e.g., the plant remains vegetative). Opposite to quantitative response.

Quantasomes : Quantasomes are particles found in the thylakoid membrane of chloroplasts in which photosynthesis takes place. They are embedded in a para crystalline array on the surface of thylakoid discs in chloroplasts. They are composed of lipids and proteins that include various photosynthetic pigments and redox carriers.

Radiant energy (Q_e, J): The transfer of energy of radiation.

Radiation frost: Heat radiated from surface of soil, trees, and any other solid particles to reduce the temperature low enough to cause frost conditions. Solid particles lose heat more rapidly than air, reducing the surface temperature. Eventually the air at low levels becomes cool and heavy compared to air at higher elevations. Occurs more readily on cloudless nights when there is no barrier for retaining the heat (i.e., a barrier that radiates the heat back to earth).

Radiation: The emission and propagation of electromagnetic waves or particles through space or matter.

Radical (Free Radical): An atom or a group of atoms with an unpaired electron which can exist independently for short period during the course of chemical reaction.

Radicle: Embryonic root of seed plants.

Salicyclic acid: Salicyclic acid (from Latin salix, willow tree, from the substances used to be obtained) is aminohydroxybenzoic acid, a type of phenolic acid and a beta hydracid. It has the formula C₇H₆O₃. This colourless crystalline organic acid is widely used in organic synthesis and function as a plant hormone. It is derived from the metabolic of salicin. In addition to being an important active metabolic of aspirin (acetylsalicyclic acid), which acts in part as a prodrug to salicyclic acid, it is probably best known for its use as a key ingredient in topical anti-acne products. The salts and esters of salicyclic acid are known as salicylates.

Salination: The process of accumulation of soluble salts in the soil.

Saline adaptation: Genetic modification of individuals in a population that increases their ability to survive excess salt.

Saline adjustment: Physiological and biochemical changes of individual plants that increase their ability to survive excess salt.

Tannins: Group of plant phenolic compounds found in higher plants as secondary metabolites. Their main function is to defense against microorganisms, insects, and herbivores and in allelopathy.

Taxis (tactic orientation; formerly topotaxis): Movement of motile organisms, cells or organelles, the prevailing direction of which is determined by the direction of the stimulus.

TATA box (Hogness box): A sequence of nucleotides which serves as the main recognition site for the attachment of RNA polymerase in the promoter region of eukaryotic genes. Located at around 25 nucleotides upstream of the transcriptional start site. It consists of seven base consensus sequence, TATAAAA.

TCA cycle: Tricarboxylic acid cycle. It is also called as citric acid cycle or Krebs cycle, It is a step in aerobic degradation of glucose to convert into energy. During this cycle several intermediates are produced, which leads to several metabolic pathways. During this cycle, there is production of reductancts such as NADH, FADH and GTP.

Telomere: Sequences at both termini of each eukaryotic chromosome that facilitate replication.

Ubiquinone (UQ): It is a lipophilic metabolite that functions in the electron transport chain in the plasma membranes of prokaryotes, and the inner mitochondrial membranes of eukaryotes, apart from its roles as an antioxidant and in the regeneration of tocopherols. Also called as Coenzyme Q.

Ubiquitin: It is a small protein that is found in almost all cellular tissues in all eukaryotic organisms,( i.e. it occurs ubiquitously) which helps to regulate the processes of other proteins in the body.

Ultracentrifuge: A high speed centrifuge with speed upto 60,000 rpm and centrifugal field of 500,000 x g