eChapters

1.1. WEATHER AND TILLAGE

Weather : A state or condition of the atmosphere at a given place and at a given instant of time'

Climate : The generalized weather or summation of weather conditions over a given region during comparatively longer period

Meteorology : Greek word “Meteoro” means 'above the earth's surface' (atmosphere) and “logy” means “indicating science”. Branch of science dealing with that of atmosphere is known as meteorology

Agricultural meterology : Branch of applied meteorology or a branch of agriculture as it deals with agriculture

Coordinates of India : 8^o N and 37°N latitude; 68°E and 98°E longitude

Coordinates of Tamilnadu: 08°05' N and 13°35' N latitude; 76°15' E and 80°20' E longitude

Hydrosphere - water portion of the earth

Lithosphere - solid portion of the earth

Atmosphere - gaseous portion of the earth

Atmosphere : It is the colourless, odourless and tasteless physical mixture of gasses, which surrounds earth on all

4.1. PESTS OF FIELD CROPS

Insect pests are the major constraints limiting agricultural productivity growth. It is estimated that herbivorous insects eat about 26 percent of the potential food production. Emerging problems of insecticide and disease resistance, secondary pest outbreak and resurgence further add to the cost of plant protection. Annual crop losses due to insect pests and diseases in India are estimated to be 18 percent of the agricultural output. Main causes of emerging pest and disease are favourable prevailing weather condition, absence of natural enemies, abundant food supply, use of pesticides, use of fertilizers and irrigation.

PESTS OF RICE

Borers and Defoliators

Large quantities of crop residues are produced and if properly used, they can provide cost effective means for supplying organic matter, plant nutrients and improved soil health. The highly lignocellulosic nature of crop residues indicate their potential role in maintaining soil organic matter and enriching the soils with N-rich microbial biomass resulting from decompositions. However, their indiscriminate handling often burning leads to decline in soil health, air pollution and overall loss. Since most crop residues find use as feed and fuel, efficient recycling of the remaining amount can have very significant and positive effect.

Large quantities of crop residues are produced and if properly used, they can provide cost effective means for supplying organic matter, plant nutrients and improved soil health. The highly lignocellulosic nature of crop residues indicate their potential role in maintaining soil organic matter and enriching the soils with N-rich microbial biomass resulting from decompositions. However, their indiscriminate handling often burning leads to decline in soil health, air pollution and overall loss. Since most crop residues find use as feed and fuel, efficient recycling of the remaining amount can have very significant
and positive effect.
The data regarding five major crops are shown. Even after use of some of them as animal feed they offer a great opportunity of using them back in to the soils which are hungry for organic carbon and other matters. Practice of Crop Residue Burning
The problem of collection and transport of crop residue and the short timebetween harvesting of one crop and making the farm free for the second crop has led to the harmful practices of crop residue burning. If instead of burning it, the residues can be incorporated into soils, a host of heterotrophic microorganisms bring about minor discharge of carbon and other elements contained in plant residues. A large increases in beneficial soil microbial populations and organic carbon can be achieved

Rice-wheat (RW) is the major cropping system occupying about 10.5 mha in the IGP of India. It contributes more than 60% of the foodgrains to the central pool. With shrinking land resources and burgeoning population, the RW system will be under pressure to produce more grain output per unit area in the coming decades. Meeting this challenging task requires sustainable management of soil, water and plant nutrient resources. High yields of the irrigated RW system result in production of huge quantities of crop residues. Total production of crop residues in Punjab is about 47.2 mt which includes paddy straw, wheat straw, cotton sticks, sugarcane leaves, maize stalk, and other oilseeds and pulse residues (Beri and Gupta, 2003). Wheat and rice straw constitutes more than 70% ofthe crop residues produced in the country. Paddy straw alone constitutes more than 50%. Cotton and sunflower residues are generally used as fuel. Sugarcane trash (leaves) is generally burnt in-situ or used as fuel after collection from the field. Increasing constraints of labour and time have led to the adoption ofmechanized farming in the highly intensive RW cropping system. Approximately 91% ofthe total rice area is mechanically harvested, while 82% of the total wheat area is mechanically harvested. Traditionally, wheat and paddy straws have been removed from the fields for use as cattle feed and for several other purposes such as livestock bedding, thatching material , for houses, and fuel. While more than 80% ofwheat residue is collected by the farmers after combine harvesting and often fed to animals, paddy straw is considered poor feed for animals due to its high silica content.

Substantial loss ofplant nutrients (especially N and S) and organic carbon occurs during burning of crop residues, with important implications to soil health. About 40% of the N, 60-85% of the K, 30-35% of the P, and 40-50% of the S absorbed by rice remains in the vegetative parts at maturity. One tonne of paddy straw contains approximately 6-7 kg of N, 1.0-1.7 kg of P₂O₅ and 14-25 kg K₂O. Apart from huge loss of precious plant nutrients, burning of crop residues depletes soil health. Air pollution from stubble burning also impacts human and animal health both medically, and by traumatic road accidents due to restricted visibility. In view ofthe serious problems associated with the residue burning, new ways are being sought to efficiently utilize the huge amount of surplus residues produced in the country.

11.1 Biomass

Globally, all agricultural countries have promoted the use of biomass sources for many household applications and biomass energy generation. Biomass is defined as the bio residue available from the sum of crop production, agricultural waste, vegetation, forestry waste and organic waste. Biomass is a renewable source of energy and contains a complex mixture of carbon, nitrogen, hydrogen, and oxygen. Various biomass resources are available in different parts of countries and are classified based on their availability. The broad classification of biomass energy is in three formats; residue of agricultural crops, energy plantations, and municipal and industrial waste. Agriculture residues are organic materials produced as the byproduct from processing and harvesting of agriculture crops. 

Indian crop production system excels in front of several biophysical adversities commonly known as biotic and abiotic stress.  Water is the principal factor limiting crop yield and about 2/3 of total cultivated landing India comprise of Dry land agriculture primarily under rainfed conditions with no or limited water supply system.  The Indian production systems are dominated by cereals, primarily rice maize, sorghum, pearl millet other coerces and fine cereals leguminous (urd bean, mung bean, peanut) and oil yielding crops during kharif and  wheat barley chickpea, lentil and forage legumes in rabi  season.  The production systems are generally characterized by cereal/legume mixed-cropping dominated by maize, millet, sorghum and wheat. The major constraints in both regions to crop production are low soil fertility, insecure rainfall, low-productive genotypes, low adoption of improved soil and crop management practices, and lack of appropriate institutional support. choice of crop  is important but selection of right varieties is utmost  important because  varieties which have proven excellent in irrigated or high rainfall areas are generally not suited for limited irrigated conditions.

Introduction

Through the use of both art and science, crop breeding is the process of enhancing significant agricultural plants for the benefit of humanity. Crop breeders attempt to improve the productivity and nutritional value of our food, f iber, pasture, and industrial crops via their efforts. In order to meet the needs of a growing global population with rising dietary demands, crops are essential. Additionally, the activity of crop breeders contributes to the improvement of environmental protection.

Since the beginning of agriculture, farmers have been selecting plants for desirable characteristics such as bigger seeds, more flavourful fruits, and other desirable characteristics. This method is known as plant breeding. In today’s world, the breeding of plants is a collaborative effort between scientists and farmers.

Different techniques are used by plant breeders, depending on the manner of reproduction of crops. This process is known as self-fertilization, and it occurs when pollen from one plant fertilizes the reproductive cells or ovules of another plant. There is a phenomenon known as cross-pollination, in which pollen from one plant can only fertilize another plant. For example, runners from strawberry plants are an example of asexual propagation, in which the new plant is genetically identical to its parent plant. Apomixis, also known as self-cloning, is a process in which seeds are created asexually and their offspring are genetically identical to their parents. When it comes to developing appropriate breeding and selection strategies, the mode of reproduction of a crop is the decisive element. This is because the genetic makeup of the crop is determined by the mode of reproduction. Additionally, it is necessary to have knowledge of the way of reproduction in order to artificially manipulate it in order to produce enhanced varieties. The only breeding and selection strategies that are appropriate for a crop are those that do not disrupt the crop’s natural condition or guarantee that it will remain in that form. The imposition of self fertilization on cross-pollinating crops results in a significant decrease in the performance of such crops for several reasons, including those listed above.

Introduction

The crops, its significance along with its classification has got paramount importance in agricultural heritage. A crop is a plant or animal product that can be grown and harvested in an area with a target to earn profit or achieve subsistence. Crop may refer either to the harvested parts or to the harvest in a more refined state (husked, shelled, etc.). Most crops are cultivated in agriculture or aquaculture.

A crop is usually expanded to include macroscopic fungus (e.g. mushrooms), or alga (alga-culture) at the point of origination. Most crops are harvested as food for humans or livestock (fodder crops) or to get raw materials for agro-based industry. Some crops are gathered from the wild collection (including intensive gathering). The important non-food crops include horticulture, floriculture and industrial crops. Horticulture crops include plants used for other crops (e.g. fruit trees, grown single or in orchard). Floriculture crops include blanket plants, houseplants, flowering garden and pot plants, cut cultivated greens, and cut flowers. Industrial crops are produced for clothing (fiber crops), bio-fuel (energy crops, algae fuel), or medicine (medicinal plants).

Microbes (fungi, bacteria or viruses) are rarely referred to as crops. Animals raised for human or animal consumption are referred to as livestock and microbes as microbiological cultures. Microbes are not typically grown for food itself, but are rather used to alter food (e.g., for production of citric acid, fermenting yogurt, soya sauce and so on). The importance of a crop varies greatly by region. Crop production depends on the availability of arable land and is affected in particular by yields, macroeconomic uncertainty, as well as consumption patterns; it also has a great incidence on agricultural commodities’ prices. The importance of crop production is related to harvested areas, returns per hectare (yields) and quantities produced. Crop yields stands for harvested production per unit of harvested area for the particular crop i.e. products. In most of the cases yield data are not recorded, but are obtained by dividing the production data by the data on area harvested. The actual yield that is captured on farm depends on several factors such as the crop’s genetic potential, the amount of sunlight, water and nutrients absorbed by the crop, the presence of weeds and pests infestation. These indicators are presented for wheat, maize, rice and soybean. Crop production is measured in tons per hectare, in thousand hectares and thousand tons.

Agricultural systems are complex, and understanding this complexity requires systematic research under shrinking agricultural research resources. Field experimentation can only be used to investigate a very limited number of variables under a few site-specific conditions. The crop growth simulation models simulate crop growth, development and yield taking into account the effects of weather, genetics, soil water, carbon and nitrogen, planting, irrigation and fertilizer (e.g. Nitrogen, Phosphorus) management. Ofthe many factors that potentially affect the growth of plants, the two that are most responsive to management are water and nitrogen. It is therefore not surprising that most crop models include routines to handle responses to water and nitrogen. Less frequently do models attempt to describe limitations due to other soil constraints (Probert and Keating, 2000). In the context of integrated nutrient management, the performance of a crop model depends mainly on its ability to adequately describe the release of nutrients from diverse inputs and their uptake by the crop.

Origins and genesis of a crop simulation model

Crop simulation model approach was started near about 50 years ago, in early 1960s when early simple crop models were developed for estimation of transpiration and photosynthesis. The first step towards crop modeling was the development of simple models to estimate light interception and photosynthesis (Loomis and williams, 1963; De wit, 1965 and Duncan et al., 1967). There are many crop growth simulation models. Some are more generic in nature while others are built for specific purposes. Most of these models simulate crop growth and soil processes using daily time steps. All models are developed with some assumptions and hypotheses, and all have strengths, weaknesses and limitations for appropriate application. Well-known crop modelling groups across the world include IBSNAT/IFDC (International Benchmark Sites Network for Agro technology Transfer/International Fertilizer Development Centre) in USA, WAU/AB-DLO (Wageningen Agriculture University/Centre for Agro-biological Research) in the Netherlands, and APSRU (Agriculture Production Systems Research Unit) in Australia. The IBSNAT project was initiated in 1982, and over the past 20 years it has developed more than 15 models, including CERES (Crop Estimation through Resource and Environment Synthesis) Rice and CERES Wheat, which are available either as stand-alone models or within the DSSAT (Decision Support System for Agrotechnology Transfer) shell (Uehara and Tsuji, 1993).

5.1 Introduction

A Crop Simulation Model is a mathematical model which describes crop growth and development processes as a function of environment, soil conditions, and crop management. Simulation model is a schematic representation which works on set of underlying assumptions, equations and algorithms, closely replicating the behaviour of the agricultural systems. A crop growth simulation model predicts the harvestable yield. Apart from this final state of crop production, the model also provides a host of quantitative information about major processes involved in the various stages of crop development. The information covers each component of the crop such as leaves, stems, roots and harvestable products as they change over time, including the changes in soil moisture and nutrient status.

An increase in the population, demands an increase in agricultural production with available resources. Efficient management of available resources under varying weather conditions is important for increasing agricultural productivity. Besides that, the emphasis of agricultural production changes from quantity to quality and sustainability (Aggarwal et al., 2000). Solution of these new challenges lies in understanding the interaction of the numerous elements affecting the plant growth and generating a crop growth model. This extremely complicated information needs to be processed and interpreted on a spatial scale. Information technology which has unleashed new frontiers in data analysis and automation is the driving force behind this model generation. These powerful computer programmes simulate the crop growth or yield of crops under various management regimes and provide near real time information to help farmers to make strategic decision in the management of their crops.

The susceptibility and vulnerability of crops to diseases are critical factors that determine the impact of disease outbreaks on agricultural productivity and food security. Crop diseases can have devastating effects on crop yields, quality, and marketability, resulting in significant economic losses for farmers and the agricultural industry as a whole. The susceptibility of crops to diseases refers to the inherent characteristics of the crop that make it more or less prone to infection by a particular diseasecausing agent. This can include factors such as the crop’s genetic makeup, its physiological state, and its environmental conditions. For example, some crop varieties may have a natural resistance to certain diseases, while others may be more susceptible due to their genetic characteristics. Vulnerability, on the other hand, refers to the degree to which a crop is exposed to disease-causing agents and is unable to withstand or recover from disease outbreaks. This can include factors such as the crop’s location, climate, soil type, and farming practices. For example, crops grown in areas with high disease pressure, inadequate soil moisture, or poor farming practices may be more vulnerable to disease outbreaks. Understanding the susceptibility and vulnerability of crops to diseases is essential for developing effective disease management strategies. By identifying the factors that contribute to a crop’s susceptibility and vulnerability, farmers and agricultural experts can take proactive measures to prevent or mitigate disease outbreaks. This can include using disease-resistant crop varieties, implementing integrated pest management practices, and adopting sustainable agricultural practices that promote soil health and biodiversity. In this chapter, we will explore the concept of susceptibility and vulnerability of crops to diseases in more detail, including the factors that contribute to these phenomena and the strategies that can be used to manage and mitigate disease outbreaks. By understanding the complex interplay between crops, diseases, and environmental factors, we can develop more effective and sustainable approaches to disease management that promote agricultural productivity and food security.
4.1 Factors Determining Susceptibility
The susceptibility of crops to diseases is determined by a complex interplay of factors, including genetic, physiological, and environmental factors. Genetic factors play a crucial role in determining the susceptibility of crops to diseases. Some crop varieties may have a natural resistance to certain diseases, while others

Introduction

The literary meaning of voyage is a long journey by water or air to a distance place. The crop voyage means the introduction of different crops from outside and movement of the crops originated in India to abroad. India is one of the mega agro-biodiversity countries of the world. Many plant species have been domesticated here. The agro-biodiversity of the indigenously domesticated higher plant species was further enriched with introduction of exotic crops since ancient times, as reflected by the presence of American cereals such as maize and amaranths, African cereals such as pear millet and sorghum, West Asian legumes such as field pea, grass pea and chickpea, and Chinese proso millet and buckwheat in the archeological remains and/or in ancient Indian agriculture writings. Most of these crops have acclimatized and adapted to diverse ecological conditions offered by the Indian Sub-continent to such an extent that many appear natural to the land, and have thrown enormous genetic diversity, making India either a secondary center of diversity for crops such as pearl millet, sorghum, maize, amaranths, cowpea, niger, safflower, muskmelon, pumpkin, chilies and others or regional center of diversity for crops such as barley, grain amaranth, buckwheat, pearl millet, foxtail millet, chickpea, bottle gourd and others. All details of crop voyage has already been discussed in the relevant topic of discussion (Chapter 8) on “Journey of agriculture and its development from past to modern era.”

The Crop Weather Calendar (CWC) is arguably one of the most practical and indispensable tools developed within agricultural meteorology. It transcends simple weather data by synthesizing comprehensive information about a specific crop’s entire life cycle with the historical climate patterns and recommended agricultural practices for a particular geographical area, typically an agro-climatic zone or even a district. More than just a timetable, it serves as a strategic blueprint that guides farmers and agricultural professionals toward optimized, resilient, and sustainable farming (Fig. 4.1).Imagine it as a detailed annual planner for a specific crop, where every entry is backed by decades of climate data and agronomic research. 4.2 Crop Weather Calendar: A Deeper Dive

Introduction 
Building upon our foundational understanding of how weather intrinsically shapes crop development, from the micro-scale physiological responses to the broader patterns revealed by Indigenous Technical Knowledge, we now transition to a chapter dedicated to a highly practical and actionable synthesis of this critical interrelationship: Crop Weather Calendars. These calendars are far more than mere chronological charts; they represent systematically organized and dynamic compilations of meteorological information meticulously integrated with precise crop-specific data, designed to serve as an indispensable guide for optimizing agricultural practices. In this chapter, we will embark on a comprehensive exploration of Crop Weather Calendars, moving beyond the often informal or culturally embedded ecological calendars previously discussed. We will delve into how these powerful tools systematically integrate historical weather patterns, which involves analyzing longterm meteorological data to establish reliable averages and identify probabilities of specific weather events, such as the typical onset of monsoons, average frost dates, or periods of peak solar radiation. They also incorporate real-time meteorological data, bringing in current weather observations to track actual conditions against historical norms and initial forecasts. Furthermore, Crop Weather Calendars utilize future weather forecasts, drawing on short-, medium-, and long-range meteorological predictions to anticipate upcoming conditions (Fig.12.1). This integrated weather information is then critically aligned with the precise phenological stages of a given crop cultivar, recognizing that a crop’s sensitivity and requirements vary significantly throughout its life cycle. Our exploration will detail the essential components that constitute a robust crop weather calendar, including the identification of crucial growth periods, pinpointing the most sensitive and influential developmental stages of the crop like germination, tillering, flowering, and grain filling, where weather impacts are most pronounced. It also involves the establishment of weather thresholds, which means defining the optimal, critical, and damaging ranges of key weather

Variation in field crops between years is associated with many factors. This is mainly due to weather, soil and management factors. There is complex reaction of weather variables among themselves as well as with other factors. Therefore, many attempts were made to study the effect of weather variable on crop yield through simulation modeling.

Climate, soil, input and management factors influence the crop yield. Weather is the most important natural input that affects the agricultural production and productivity. The agricultural activities starting from the land preparation to harvest and post-harvest storage are greatly influenced by the weather. The effects of weather on crops may be direct such as those of precipitation, solar radiation, humidity, temperature, etc., or indirect such as those of pest, diseases, weed competition, etc. Thus, the success or failure of a crop is determined by the prevailing weather conditions. Although influence of weather conditions on yield is well established, the quantitative assessment is not always straight forward and simple. The quantitative assessment of the effect of weather on crops is an important application of agrometeorology. The relationship between weather and crop production has been understood through crop weather modelling and study on this aspect through a systematic approach started a century ago. The aim of developing crop weather models is to ensure better utilisation of resources and hence a more environmental friendly and sustainable agriculture.

A model is a schematic representation of the conception of a system or an act of mimicry or a set of equations, which represents the behaviour of a system. Its purpose is usually to aid in explaining, understanding or improving performance of a system. Agricultural models are mathematical equations that represent the reactions occurring within the plant and the interactions between the plant and its environment. However, it is a difficult task to represent any system completely in mathematical terms because of the complexity of the system. Universal models do not exist for the agricultural systems and agricultural models are built for specific purposes and the level of complexity is accordingly adopted. Different models are developed for different subsystems and several models may be built to simulate a particular crop or a particular aspect of the production system. Crop weather models may be defined as a simplified representation of the complex relationships between weather or climate on one hand and crop performance such as growth, yield or yield components, on the other hand by using mathematical and/or statistical techniques