eChapters

The ever mounting population in 21^st century is a great challenge for the researchers to provide ample food and that has to be achieved within the context of existing challenges such as deteriorated arable land along with increasing adverse affects of changing climate. There is demand to increase food production to the tune of 70% by 2050 (Wani and Sah, 2014). Although major crops have achieved good progress, vulneRability to climatic variability emerged as a serious concern in crop improvement which could be attributed to higher sowing densities that in turn lead to more competition for water and nutrients. Abiotic stresses can be considered as major yield restraining factors among different crops. The projected estimations for changes in abiotic stresses such as drought, water logging and heat reveals far serious concerns for crop productivity (Qin et al., 2011; Bailey-Serres et al., 2012). Therefore, the concern of global food security in the era of climate change has compelled plant scientists in different crops to shift to breeding for climate resilient genotypes. Maize, being a hardy crop has an inherent potential to perform well under sub-optimal environments with minimum crop management (Kole et al., 2015). Abiotic stresses such as drought, heat and water logging affects maize yield adversely.

Although, conventional breeding approaches have exploited its fullest potential for production of elite maize hybrids but still little success attained for breeding climate resilient genotypes or varieties owing to the fact that stress tolerance is multi-genic or quantitative in nature. Therefore, the best option is to utilize the molecular breeding along with the conventional approaches for development of climate smart varieties.

Maize occupies an important position in the world economy, and serves as an important source of food and feed (Gupta et al., 2015a). Together with rice and wheat, it provides at least 30% of the food calories to more than 4.5 billion people in 94 developing countries (Shiferaw et al., 2011). In India, maize is an important cereal too, and is grown on an area of 9.2 million hectares with production of 24.2 million tonnes (www.indiastat.com). The demand for cereals will continue to increase as a consequence of the expanding human population. The world will have around 7.7 billion people by 2020, and it will reach up to 9.3 billion by 2050, and the demand for maize between now and 2050 will double in the developing world (Rosegrant et al., 2009). By 2025, India too would require to double the production (50 million tonnes) of maize grain to meet the domestic demand (Yadav et al., 2016).

Malnutrition caused by inadequate consumption of balanced diet has emerged as one of the alarming problems especially in the under-developed and developing world. Mostly the resource-poor suffer from ‘hidden hunger’, a term often used to describe malnutrition caused due to micronutrient deficiencies in staple food diet (Bouis and Welch, 2010).

An estimated two billion people suffer from micronutrient deficiency, while 795 million people are undernourished (IFPRI, 2016a). Of the 667 million children under the age of five worldwide, 159 million are stunted, while 50 million do not weigh enough for their height (IFPRI, 2016b). An estimated 45% of deaths of children under age five are linked to malnutrition (Black et al., 2013). Malnutrition contributes to global burden of disease, and loss in annual gross domestic product (GDP) in Asia and Africa to extent of 11%. South Asia is home to more than 35% of the world’s poor, and 21.9% of the population of India lives in poverty, and thus vulnerable to various health problems (IFPRI, 2016a). 15.2% of the people in India are undernourished, and more than one third of the world’s underweight malnourished children live in India, posing severe socio-economic loss to the country.

The ability to fast-track development and delivery of improved maize cultivars with capacity to provide climate-resilience (high and stable yields in stress-prone environments), coupled with improved nutritional quality, will be critical for sustainable intensification and diversification of maize-based cropping systems, and for providing enhanced income opportunities to the smallholders. This warrants coordinated multi-institutional efforts and implementation of innovative strategies to further increase genetic gains through breeding, and to translate these gains in the farmers’ fields. This article will focus only on the novel tools/ technologies/strategies that are being employed by CIMMYT for increasing genetic gains, especially for grain yield under stress-prone environments in the tropical/sub-tropical regions of sub-Saharan Africa, Latin America and Asia.

Novel tools/techniques/strategies for increasing genetic gains in the tropics

“Genetic gain” (also called as selection response) refers to the difference in the mean value of the selection criterion between original generation and next generation (formed from only the selected individuals), when they were compared in the same environment. The selection criterion is the trait(s) on which selection is based. While conventional breeding has been successful in improving maize yields over the decades, and especially in the last one decade in India through single-cross hybrids, the significantly rising demand for maize in the tropical regions of sub-Saharan Africa and Asia warrants sharp increases in genetic gains. Thus, the major challenge for the present generation of product development teams is to double the genetic gains for grain yield under stressed environments, i.e., from the present <1% to at least 1.5% within the next 5-6 years.

Maize (Zea mays L.) occupies an important place in world agriculture due to its high yield potential and greater demand. Because of its divergent character, maize is grown over a wide range of climatic conditions, ranging from near sea-level to several thousand meters above sea-level (2,700 msl). It can also be grown in all types of soils ranging from sandy to heavy clay. Among the factors adversely affecting productivity, incidence of diseases is prominent. In India Maize is prone to a number of biotic stresses like foliar diseases, downy mildews, banded leaf and sheath blight, stalk rots and ear rot caused by fungi and bacteria, incidence of which are variable in time, space, and genotype. Disease may be minimized by the reduction of the pathogen’s inoculum, inhibition of its virulence mechanisms, and promotion of genetic diversity in the crop (Richard et al., 2005). Conventional plant breeding for resistance has an important role to play that can now be facilitated by marker-assisted selection.

Chemical control measures for some of the diseases are helpful in reducing losses, however for stabilizing production it is necessary to build level of genetic resistance. Germplasm improvement programme undertaken in sixties and early seventies by All India Co-ordinated Maize Improvement Project provided an opportunity for combining resistance against important diseases with other desirable agronomic traits. Thus, breeding for resistance had been an important objective of the overall crop improvement programme and it had been a cooperative venture of the plant breeders and plant pathologists. Consequently, it was recognized that there should be an efficient technique for the mass multiplication of inoculums, artificial inoculation technique and scoring/rating of plant disease as a pre-requisite for the successful identification of resistant sources in such improvement programme. With these objectives in to consideration, a six days seminar on the “Techniques of scoring for resistance to diseases of maize in India” was held at Andhra Pradesh Agriculture University, Hyderabad during 15-20 March, 1982 (Payak and Sharma, 1983).

Maize (Zea mays L., 2n=20) is a cereal crop that is grown widely in more than 165 countries in a range of agro-ecological environments. Even in Asia, the rapid increase in maize acreage in the last decade is an indication that it is winning the battle as compared with rice. The Asian region will see itself as a major global player in the near term. In the past it was mainly confined to food in India and many other countries however, now it has become the industrial crop. Maize has several industrial applications and more than 1000 products are being developed from maize in India and around 3500 products in USA and other countries. It is a raw material for many of the important industries viz. pharma, textile, paper, film, tyre food, processing, packing and biofuel, etc. The growth rate of poultry, livestock, fish, wet and dry milling industries are very high therefore, maize demand will continue to increase in year to come.

Global Maize Scenario

Globally, maize is primarily used as feed livestock and has many industrial uses; however in many developing countries it is still used as a food crop. Small-scale farmers in both sub-Saharan Africa and Mesoamerica generally grow maize as a food crop for household consumption and for saline urban markets. Maize is particularly important in the diets of the rural and urban poor in sub-Saharan Africa and Latin America. Globally, maize is grown in 165 countries in a total of 185.1 million hectares area with 1018.1 million tones of production and 5.52 tonnes/ha productivity (Anonymous 2015-16). Almost 70% of the total maize production in the developing world is coming from low and lower middle income countries. In Asia, maize has recorded the fastest annual growth (around 4%), as compared to other cereals. Maximum maize production was in USA (353.7 million tonnes) followed by China (218.6 million tonnes) and Brazil (80.3 million tonnes) (Fig. 1), while the area under maize cultivation was in China (36.3 million hectare) followed by USA (35.5 million hectare) and Brazil (15.3 million hectare) (Fig. 2). The average world maize productivity is 5500 kg/ha, but the highest productivity of maize was achieved in USA (9970 kg/ha) followed by Canada (9591 kg/ha) and France (8137 kg/ha) (Fig. 3).

Maize (Zea mays L.), the “Queen of Cereals” is one of the most important highly evolved coarse cereal crop originated at Mexico. This is most widely distributed crop of the world cultivated predominantly in tropics and sub-tropics right from sea level to 4000 m altitude as irrigated or rainfed crop. The demand for maize as an animal feed will continue to grow faster than the demand for its use as a human food, particularly in Asia, where, doubling of production is expected from the present level of 165 m t to almost 400 mt.

Maize (Zea mays L.) is the third most important crop of country after rice and wheat and is cultivated round the year. Its grain is used as feed, food and industrial raw material. Enormous progress has been made during last six decades to enhance yield potential through genetic improvement and alleviate effects due to various biotic and abiotic-stresses. In India, it is an important crop not only in terms of acreage but also in context to its versatility for adoption under wide range of agro-climatic conditions. Of the different forms used for human consumption, 45% is consumed as staple food in various forms viz., bread, biscuits, cookies or transformed into corn flakes, soups, fresh-roasted sweets, boiled cobs and vegetables etc. Maize grain is main ration for poultry birds while forage maize is used as fresh or dry fodder for dairy industries. In Rajasthan maize occupies 0.89 m ha area with an annual production of 1.55 mt and productivity of 1.74 t/ha (Govt of Rajasthan, 2015). Being major Kharif crop in Rajasthan, the productivity levels of maize are still below the national average and farmers are not getting better economic returns. However, profitability can be accelerated further by growing recently popular speciality corns.

Maize ranks fourth after rice, wheat and bajara with respect to area and production, and grown on 4.23 lakh ha average with 6.72 lakh tones production and yield 1589 kg/ha in the Gujarat (2014-15). The state has 38.0% lower than national yield. It mainly grown in Panchmahal, Dahod, Mahisagar, Vadodara, Chhota Udepur, Kheda, Sabarkantha, Banaskantha and Aravali districts as rainfed Kharif and irrigated winter/Rabi crop for food, feed and industrial raw materials.

It is staple food and feed of tribal and grown as sole and intercrops with pigeon pea, black gram and soybean in Kharif season. The white and yellow flints to semi-flint maize are preferred to prepare bread and other food preparations

The state of Madhya Pradesh is one of the high profile maize growing state of the country cultivating maize in about 11.32 lakh hectare area which is ~12% of the total maize area of the country having 90-95% of total maize area having rainfed. Madhya Pradesh is situated in heart of India between 17°-26° N latitudes and 74°-84° E Longitude. The rainfall in maize growing belt varies from 800 to 1600 mm. Due to erratic and uneven rainfall in the state, the production and productivity of maize fluctuates every year. Maize cultivation in the area is associated with resource poor tribal farmers. As the demand for maize is growing globally due to its multiple uses for food, feed and industrial uses, we need to produce more from same or even less resources, which can be achieved through targeting technologies in potential regions.

Besides, monsoon crop due to mild winter conditions the climate allows the cultivation of maize during winter successfully under assured irrigation conditions. At present about 50 thousand ha area is under Rabi cultivation with high productivity levels as compared to monsoon crop. However, the major area increase was achieved during past few years mainly due to adoption of hybrids and shift in acreage under non-traditional areas, replacing soybean crop on farmers field. Uncertain climatic conditions and more disease and pest problem lead farmers to adopt maize in place of soybean.

The trends in area production and productivity of maize in Madhya Pradesh has shown a remarkable increase during four decades. During 1966-67 the maize acreage in the state was very less (5.59 lakh ha) that has grown up by 11.32 lakh ha in 2014-15. Moreover, the productivity also increased dramatically from mere 811 kg/ha during 1966-67 to 1513kg/ha in 2014-15.

Maize (Zea mays L.) is the third most important grain crop in India after rice and wheat with respect to area and production. It has wide ecological adaptability and is grown in almost all parts of the country extending from extreme semi-arid to sub-humid and humid regions. The crop is also popular in low and mid-hill areas of Western and North Eastern regions. It has the highest yield potential and used as human food, animal feed and as a source of large number of industrial by-products. Hence, it is called as “Queen of cereals”. In India, about 59% of the total production is used as feed, while the remaining is used as industrial raw material (17%), food (10%), exports (10%), and other purposes (4%).

Tamil Nadu has a total geographical area of 13 million hectares with a coastal line of 922 km and is endowed with 3 per cent of water resources of the country. Out of 13 million hectares of geographical area, the cultivable area in Tamil Nadu is around 7 million hectares and 55 per cent of which is dryland. The State has gross irrigated area of 33.94 lakh ha out of which 79% is under food crops and 21% is under non-food crops. In Tamil Nadu, maize was grown in an area of 0.14 lakh ha during 1970-71 with the annual production of 0.16 lakh tonnes, mainly concentrated in Tanjore, Pudukkottai and Trichy districts. Due to rapid increase in the demand of maize for poultry and animal feed, industrial uses and introduction of high yielding varieties and hybrids, the area under maize has gone up to 3.8 lakh ha with the production of 22.45 lakh tonnes during 2013-14. The major maize growing districts are Perambalur, Tuticorin, Dindigul, Erode, Karur, Ariyalur, Salem and Southern districts of Tamil Nadu. The demand and production of maize is increasing more rapidly as compared to other major commodities. It is estimated that the demand for maize will continue to increase in coming days (Yadav et al., 2016). Thus, in the next 10 years there is a necessity and opportunity for doubling India’s maize production from the current level of approximately 26 million MT.

Maize production in India has been dominated by erstwhile Andhra Pradesh and Karnataka which together contribute around 38 per cent of the total maize production of the country. Erstwhile Andhra Pradesh has achieved the highest mean yield of 4441 kg/ha in the country during the last decade (2001-02 to 2010-11) by surpassing Karnataka which had the highest productivity in the country, earlier. The main reason for achieving the highest productivity in the country was due to adoption of improved production technology along with 100% area grown under hybrids. In Telangana, maize is the third most important crop after rice and cotton. It is cultivated in 5.74 lakh hectares, predominantly in Kharif season (4.54 lakh ha), with a productivity of 3.69 t/ha (2015-16).

Trends in maize area, production and productivity in the state (1950 to 2016)

The erstwhile Andhra Pradesh (including Telangana) is the non-traditional maize growing state. But, the climate of the state is very favorable for the crop and hence maize can be grown in any season in the state. However, it is mainly grown as a rainfed crop during monsoon season, concentrated in Telangana. The trends in area, production and productivity of maize in erstwhile Andhra Pradesh have shown a remarkable increase during the past six decades. During 1955-56, the maize acreage in the state was very less (1.89 lakh ha), which has been up by 5.3 times to the present (2014-15) level of 9.95 lakh hectares. The production has also increased dramatically from merely 1.14 lakh tonnes during 1955-56 to 42.36 lakh tones during 2014-15, which is nearly 37 times higher. Similarly, the productivity of maize in the state was merely 601 kg/ha during 1955-56, which has been increased to 4257 kg/ha during 2014-15 (Fig. 1).

Karnataka is India’s eighth largest state in geographical area covering 1.92 lakh sq km and accounting for 6.3% of the geographical area of the country. As per the population Census 2011, agriculture supports 13.74 million workers, of which 23.61 per cent are cultivators and 25.67% agricultural workers. A total of 123,100 km² of land is cultivated in Karnataka constituting 64.6% of the total geographical area of the state (Table 1). Of the total cultivated area in the state, about 33.0% is covered by cereals, 42% by pulses and 19% by oilseeds and 6.0% by commercial crops (Savitha and Kunnal, 2015). Agriculture employs more than 60% of Karnataka’s workforce. The large portion of agricultural land in the state is exposed to the vagaries of monsoon with severe agro-climatic and resource constraints.

Maharashtra is the third largest state in terms of area in the country located in the north-centre of peninsular India. It links the southern part of the northern plains to the southern peninsula. Maharashtra occupies the western and central part of the country with total 3.08 lakh sq. km geographical area and has a long coastline stretching nearly 720 kilometers along the ARabian Sea. The prominent physical trait of the state is its Plateau character, which has up to 1350 meters high altitude. Physiographically this state may be divided into three natural divisions-the coastal strip (the Konkan), the Sahyadri or the Western Ghats and the Plateau. The Sahyadri mountain ranges provide a physical backbone to the state on the west, while the Satpuda hills along the north and Bhamragad-Chiroli-Gaikhuri ranges on the east serve as its natural borders. It has a geographical area of 307713 sq. km and is bounded by north latitude 15°40’ and 22°00’ and east longitudes 72°30’ and 80°30’.

NBSS & LUP has divided the state into 356 soil mapping units and published a map of the soils of Maharashtra. It has broadly categorized as soils of Konkan coast, soils of Western Ghats, soils of upper Maharashtra, soils of lower Maharashtra. The soil status of Maharashtra is residual, derived from the underlying basalts. In the semi-dry Plateau, the regur (black-cotton soil) is clayey, rich in iron and moisture-retentive, though poor in nitrogen and organic matter. The rainy Konkan and the Sahyadri Range, the same basalts give rise to the brick-red laterites, which are productive under a forest cover, but readily stripped into a sterile varkas when devoid of vegetative cover. The soil in the Deccan Plateau is made up of black basalt soil. This type of soil is rich in humus. The soil is commonly known as the black cotton soil because it is best suited for the cultivation of cotton. The volcanic action which had taken place in the Deccan region has given rise to the soil texture and composition. These igneous rocks break down into the black soil which is very fertile. The Wardha-Waliganga river valley has old crystalline rocks and saline soils which make the soil infertile. This type of soil has a natural resistance to wind and water erosion because it is rich in iron and granular in structure. A very important advantage of this type of soil is that it can retain moisture. This makes the soil very reactive to irrigation.

Maize is presently the crop with growing importance in the state. Earlier it was primarily grown for human consumption only. In view of rapidly increasing demand of poultry feeds and fodder in Assam presently it has more use in some small industries. It is the raw material for most of the feed industries. Presently the crop has state acreage of 27953 hectare and production of 93179 tonnes with a productivity of 3333 kg/ha (2014-15).

While most other states in India are gradually moving away from their traditional agriculture based economy toward industry or service oriented economy, Assam is still predominantely dependent on the agricultural sector. While the sociopolitical problems afflicting the state since the last few decades are partly to blame for a lack of conducive environment for economic development of the state, particularly in industry or service oriented areas, there are various economic reasons (e.g. fragmented land) responsible for the lagging agricultural sector in the state. Economy of Assam is fundamentally based on agriculture. Over 70% of the state’s population relies on agriculture as farmers, agricultural laborers, or both for their livelihood.

Assam produces both food and cash crops. The principal food crops produced in the state are rice (paddy), maize (corn), pulses, potato, wheat, etc., while the principal cash crops are tea, jute, oilseeds, sugarcane, cotton, and tobacco. Although rice is the most important and staple crop of Assam, its productivity over the years has not increased while other crops have seen a slight rise in both productivity and acreage.

Maize is the only cereal crop which is being used as human food, animal feed and as a source of large number of industrial products. In Odisha traditionally maize is a Kharif season crop and second most important crop next to paddy during Kharif season in terms of both area and production. The Rabi maize is cultivated under irrigated condition, and accounts only 7% of total area and production of the State. While only 24% of the Kharif maize area have irrigation facilities. Irrespective of the season, it is that is the fourth most important food grain crop with respect to area in the state which is next to rice, mungbean and urdbean. Even though maize is grown as a sole crop in the state but, some farmers are also adopting maize based inter-cropping and the major recommended/adopted inter-crops are arhar, cowpea, yam, runner bean, greengram and blackgram. The comparative analysis of compound annual growth rate (CAGR) of area, production and yield of the major crops is the state was done for the years 2004-05 to 2013-14. The CAGR study of major crops revealed that no other major crop including rice has the impressive growth rate a like maize in the state (Fig. 1).

West Bengal is the fifth largest state in terms of (GSDP) Gross State Domestic Product after Maharastra, UP, TN and AP and is the third largest contributor in agriculture sector of real GDP. West Bengal has 3% of India land mass and 8% population with population density of 1029 per km².

Agriculture accounts for about 17% (2013-14) GSDP and provides employment to over 55% of workers. About 64% of the geographical area of West Bengal is under cultivation. There is little scope for further increase the current cultivable area. Because it is difficult to maintain the growth rate in the absence of adequate infrastructure support, crop diversification and market access.

Food production remained stagnant as the green revolution by-passed the state. However, there has been a significant increase in food production since 1980’s and the state is now one of the few Indian states with a surplus in food production, producing nearly 20% of the rice and 33% of potato. Agriculture accounts the largest share of the labour force. Rice, potato, jute, sugarcane and wheat are the top five crops of the state, while other major food crops include maize, pulses, oilseeds, wheat, barley and vegetables. In recent years, significant changes have occurred in maize production and utilization due to increasing commercial orientation of maize crop and rising demand for diversified end users, specially for feed and industrial uses. A sizable number of districts in West Bengal have potential for growing winter maize. Though maize favourably responds to better crop management both in Kharif and Rabi season, the erratic rainfall pattern of the south-west monsoon comes in the way of timely field operations of Kharif season. In absence of any major environmental impediments in Rabi, the desired field operations can be planned and executed at the most desired time. Moreover, the various environmental factors including absence of any major disease and insect pests in this season, helps in realizing the better profits from every additional unit of monetary inputs. Hence, future of Rabi maize in West Bengal is bright.

Maize or corn (Zea mays L.) is second most important crop after rice in Jharkhand. Though considered as a Kharif season crop, it can be successfully grown in other two crop seasons viz., Rabi and zaid also as the climatic condition in Jharkhand is conducive for growth of the plants. Rabi maize has comparative advantage over Kharif maize due to low incidence of diseases and insect pests slow growth of weeds and crop does not have to suffer on account of heavy rainfall hence, higher yield potentiality could be realized from Rabi maize. In Jharkhand, the Kharif crops including the maize are grown as rainfed as the 80 to 85% of the annual rainfall takes place during June to September. The share of maize under irrigated condition is restricted to only 15 to 18% of the total cropped area. Maize is not only an important source of nutrient to the human beings but also constitutes a basic component of animal and poultry feed. Here, farmers grow maize mainly for green cobs as cash crop whereas the grains are to be used for human consumption as well as for animals and poultry feed. The cultivation of the specialty corns like baby corn, sweet corn and popcorn is still in its infancy in Jharkhand and hence, large scale cultivation of specialty corn in the state will take some more time. Establishment of food processing unit in the state is at the nascent stage. However, the Government of India is implementing a Mega Food Park in Getalsud Industrial Area of Ranchi district in Jharkhand. The establishment of this mega food park is expected to give a significant boost to the food processing sector in Jharkhand.

Bihar is an important maize growing state in India after Karnataka, Andhra Pradesh, Telangana, Rajasthan and Maharashtra, where it is cultivated during all season. However, the yield of maize is much higher during Rabi and summer seasons than the Kharif. Due to climate change and other factors, the yield of maize is likely to further decline during the Kharif season. However, the cultivation of maize in Bihar during the Rabi season will be much more profitable as compared to wheat due to rise in temperature. There is need to develop maize varieties which can with stand biotic and abiotic due to changing climate factors.

Decadal trends of maize area, production and stresses yield in the Bihar from 1950–2015.

Chhattisgarh, the 26^th state of the Indian Union came into existence on November 1^st, 2000. The state is geographically situated in the central part of India, between the latitudes of 17° 46' N - 24° 5' N and the longitudes of 80° 15' E - 84° 20' E. Its proximate position with the Tropic of Cancer has a major influence on its climate. The total geographical area is around 137.90 lakh ha of which cultivable land area is 46.77 lakh ha and forest land area is 63.53 lakh ha with more than 2.55 crore population. In Chhattisgarh region about 22% of net cropped area was under irrigation. About 80 percent of the population in the state is engaged in agriculture and 43 percent of the entire arable land is under cultivation. Paddy is the principal crop and the central plains of Chhattisgarh are known as rice bowl of central India. Other major crops are coarse grains, wheat, maize, groundnut, pulses and oilseeds.

Importance of Maize in Chhattisgarh

Earlier maize was mainly cultivated in Surguja and Bastar division of Chhattisgarh but now it is emerging as main cash crop in entire Chhattisgarh state. There had been an increase of 20 per cent in maize crop acreage in Chhattisgarh during the past 10 years. Now the farmers of the area are cultivating maize in lines, applying atrazin weedicide, full dose of chemical fertilizers, etc. They are willing to buy the hybrid seed for cultivation from the market and taking maize as green cob and also utilizing as green fodder. Maize threshers have been purchased by some farmers in the region which is an indicative of large maize production.

For industrial utilization of the maize Chhattisgarh state has “Raja Ram Maize Factory” in Rajnandgaon district. They are producing and supplying Maize starches, liquid glucose, dextrose mono hydrate, dextrin, maltose liquid, malto dextrin, maize oil, maize gluten, maize grit, maize husk etc. But most of the maize production is used as poultry feeds in the state. Traders purchase it directly from the farmers’ fields in the villages. It is also exported to the neighboring states either as grain or green cob. Around 10-15% is retained by the farmers for own consumption and seed purpose.

Uttar Pradesh, a fourth largest state of India geographically, where agriculture is a prime occupation and this is the traditional maize growing state, accounts 7.7% of area and 5.4 percent of total maize production of the country with an average yield of 1791 kg/ha (IIMR Annual Progress Report, Kharif Maize 2015). Maize is mainly taken as a Kharif crop but, gradually Rabi maize is gaining popularity with the availability of high yielding varieties and advanced production technologies. The rice, wheat, potato, sugarcane based cropping is more popular, and maize is given a moderate priority. The current level of growth in productivity definitely fall short to meet the demand of rapidly growing population even it may increase the poverty, unless vigorous measures are taken to accelerate yield, growth, employment generation, increasing the income of farming family and ultimately targeting for the sustainable climate resilient maize production.

Maize is mainly used as a staple food and quality feed for animals. In addition to that it also serves as a basic raw material for several industries like, starch, oil, protein, alcoholic beverages, food sweeteners, pharmaceuticals, cosmetic, textile, gum, package, paper etc. A major portion of the maize produce is directly consumed as a food in the form of boiled or roasted green ears, chapattis, porridges of various forms, popcorn, cornflakes etc. and as livestock feed viz., cattle, poultry and piggery both in

the form of grain and fodder The central rachis of maize cob, to which the grains are attached remains as an agricultural waste after threshing, has many important agricultural and industrial uses. It is approximately 15 to 18% of the total ear weight and contains 35% cellulose, 40% pentose and 15% lignin (used as a raw material in cardboards). Its uses in agriculture includes as a litter for poultry and as a soil conditioner.

Maize is one of the most important food, feed, fodder and industrial crop in Haryana and is cultivated in all the three seasons (Kharif, Rabi and spring). It was cultivated on 6 thousand hectares in Kharif season with average productivity of 2.83t/ha during 2015-16. The maize is also increasing in spring season which was grown on ~ 7 thousands hectare with productivity of 4.5t/ ha. The specialty corn (baby corn and sweet corn) is also grown in >2 thousand hectare area of Haryana in national capital region. The demand of maize is increasing every year due to growth in poultry industry and expansion of maize based industries. There is a good scope of cultivation of specialty types of corn (baby corn, quality protein maize and sweet corn) in Haryana as it is very near to national capital, Delhi. The cultivation of specialty corn and its value addition by establishing

Maize is one of the most important cereal crops of the world. Being a C₄ plant, it is physiologically more efficient than rice, wheat and other important cereal crops which belong to C₃ category. In Punjab, traditionally, maize is grown during Kharif season but from last few years the area under spring maize is increasing because its cultivation is highly profitable and commercially viable after harvesting of potato crop. No doubt, Punjab has been the leading state in contributing to the national food security but simultaneously paddy-wheat rotation resulted in depletion of underground water, deterioration in soil health and environmental pollution. These problems need to be addressed for the sustainability of these natural resources and at the same time meeting the food grain production for the ever-increasing human population. Under such circumstances, maize crop is a viable alternative to replace some area occupied by rice and can help in breaking rice–wheat dominant cropping pattern in the state. Promising maize hybrids possessing high grain yield potential and offering comparable economic returns to the farmers are available with Punjab Agricultural University as well as with the private sector.

In Punjab, maize is commonly used in the form of chapatis, boiled or roasted green cob, breakfast food like cornflakes, popped grains etc. Maize chapatis are used as a delicacy with saag. The high carotene content of yellow grained maize is considered very useful in imparting yellow colour to egg yolk. Therefore, a substantial quantity of maize grain is utilized as an important ingredient of animal/ poultry feed industry. The use of maize grains for such purposes is going to increase as poultry and dairy industries are expanding. Maize plant is extensively used as green as well as dry fodder. The digestibility of maize fodder is better than sorghum, bajra and other non- legume forage crops. Maize plant does not have any anti quality factor hence can be fed to cattle at any stage. Maize can be utilized as an industrial raw material for number of industries viz., starch, ethanol, rubber, paper, cosmetics and pharmaceuticals etc. Quality Protein Maize (QPM) can be promoted for nutritional security of poor masses whereas pop corn, baby corn and sweet corn can help in increasing the farm income due to high market value. In Punjab, major industries which are utilizing maize are The Sukhjit Starch & Chemical Limited, Kapurthala, and M/s Field Fresh Food Pvt. Ltd, Ladhowal, Ludhiana.

Agriculture is the predominant sector in the economy of Jammu and Kashmir. Directly and indirectly, it supports about 80 per cent of the population besides contributing nearly 60 per cent of the state revenue. The total geographical area of the state is nearly 22.2 million hectare and population of 12.5 million, which is approximately 1.04% of the national total. The J&K is divided into three agro-climatic zones: Cold arid desert areas of Ladakh, temperate Kashmir Valley and the humid sub-tropical region of Jammu. Each has its own specific geo-climatic condition which determines the cropping pattern and productivity profile.

In Jammu province, a small portion of the land lies in the plains along the borders of Punjab while the rest of the area is hilly, dominates both in maize and wheat production. About 67 per cent of the area is under maize and wheat production with the production of 21.25q/ha maize and 15.36 q/ha wheat. This region contributes 79.56 per cent and 95.69 per cent of total production of these two cereals respectively. Even though the yield is not high, the region makes appreciable contribution to the cereals production.

The second agro-climatic zone Kashmir is also known as ‘cultivator’s paradise’. The region practically depends on irrigation, which is easily available. A large area of level land has alluvial soil. Extensive elevated plateaus of the alluvial or lacustrine material (locally called Karewas) also exist in the Kashmir valley. These Karewas are productive only in the face of sufficient rainfall or adequate irrigation facilities. Rice is the chief crop of this zone, followed by maize, oat, barley and wheat.

Ladakh zone is endowed with bare rocky mountains and bare gravel slopes. Villages are located near pockets of land with level ground and irrigation facilities, where cultivation is viable. In this region, barley is the major cereal crop followed by summer wheat. Millets and wheat rank second in importance and are grown in the warmer belt of the region.

Maize (Zea mays L.) is one of the most versatile crops having the highest genetic yield potential among cereals and wider adaptability under varied agro-climatic conditions rightly earning it the name of ‘the queen of cereals’. Maize is cultivated in all agricultural areas around the world and is an economically significant crop for all human population. It is grown from 58⁰ L north to 40⁰ L south and extends from the sea level up to an altitude of above 3,800 m; covering regions with rainfall varying from 250 to 10,000 mm (Hallauer and Miranda, 1988). Globally, maize occupies an area of about 184.0 million ha with production of 1065 million tons and productivity of 55.2 q/ha (FAOSTAT, 2014). It is the third most important cereal crop and a major source of energy, protein and other nutrients for human and livestock in the world (Jompuk et al., 2011). India is the second most important maize growing country in Asia, and now ranks as the world’s fifth largest consumer of maize. It is an important cereal crop in India covering an area of 9.42 million ha with a production of 24.35 million tonnes and productivity 25.83 q/ha (Anonymous, 2015). Maize is cultivated in the country throughout the year mostly during rainy or Kharif season (June to September, 80%) followed by winter or Rabi (November to April,18%) and spring (February to May, 2%) for various purposes including grain, fodder, green cobs, sweet corn, baby corn and popcorn.

Maize is an important crop of Uttarakhand and is cultivated in about 22 thousand ha in both hills and plains. The crop is grown for food, feed and fodder and forms an integral constituent of all major cropping systems prevalent in the state. Kharif (June-September) is the main grown season in the hills, whereas in the foothills and tarai plains, the crop is grown during zaid (Feb-May) as well. The crop is grown broadly for two different end products – grain and green ears. In areas where maize forms staple diet, the crop is grown for grain, whereas in areas adjoining/en route popular tourist destinations and towns, the crop is grown mainly for green ears. The crop is also gaining importance as an industrial crops following establishment of maize processing industry in the state.

The major maize growing districts of the state are Dehradun, Nainital, Pithoragarh, Pauri, Tehri and Almora (Fig. 1), which together comprise about 90% of total

Land is merely an area of the earth’s surface comprising all physical, chemical and biological environments that influence the land use (FAO ,1976). Land refers not only to soil but also to climate, landforms, hydrology, geology, natural vegetation including fauna and flora. The land use simply means management of a land for specific uses to meet the human needs in all rural, urban and industrial context, whereas the land use plan refers to a coherent set of decisions about the ways to achieve the desired level preferably on economic background. Thus, the land use planning is the systematic evaluation and assessment of a land and associated attributes for the purpose of identifying the best land use options beneficial to landowners or users without degrading the land resources or environment. It includes not only the landowner or users, but also the policy or decision makers as well as economic experts for financial measures from planning stage or logistic planning to execution.

Land cover

Relates to the type of feature present on the surface of the earth e.g., Fields, trees, concrete high ways.

Land use

Relates to the human activity associated with a specific piece of land. The same land would have a land cover consisting of roofs, pavements, grass and trees. The land use in an area is really an intervention by the people over the existing natural eco-environment for satisfying their needs.

Land cover is distinct from land use despite the two terms often being used interchangeably. Land use is a description of how people utilize the land and socio-economic activity - urban and agricultural land uses are two of the most commonly recognised high-level classes of use. At any one point or place, there may be multiple and alternate land uses, the specification of which may have a political dimension.

In recent times, the interpretations cover a wide spectrum of soil uses, both for agricultural and non agricultural (sewage and human waste disposal, high way construction, water and gas supply, recreation, wild life, urban and industrial structures) and many specialized uses. Soil survey if correctly carried out according to scientific principles, can provide the data base for various interpretations. This is because the same soil properties determine the behaviour of a soil for a variety of different uses. For instance, the content of clay, silt and sand, the shrink and swell behaviour, the permeability of soil to water and air, content of calcium carbonate, salts, organic matter, gypsum, soil depth, depth of ground water, hard pan formation, co-efficient of linear extensibility, water holding capacity etc. are examples of such properties that are important to plant growth and these properties also strongly influence non farm uses. Some examples in support are

A hard or petrocalcic horizon or other slowly permeable layer (clay-pan) in a soil restricts the movement of air and water, thus adversely affecting the plant root growth. Such a layer limits the soils suitability for septic tanks and other onsite waste disposal. It also makes a poor sub grade for high way construction.

A soil high in soluble salts is a poor medium for plant growth; it is also corrosive to iron and steel structures, such as pipelines and fences, causing high maintenance and repair costs.

High organic matter content is generally favourable to plant growth, but it is a limitation for road construction.

The strongly gypsiferous soils (gypsum content >10%) are considered unsuitable for arable crop cultivation because of its dissolution under irrigated or even moderate rainfall and making the surfaces uneven through the developments of sink holes. Such soils are unsuitable for irrigation and drainage canal networks and also for construction of roads, bridges etc.

The shrink- swell soils of India (vertisols) because of summer monsoon rains are suitable for growing a “kharif” crop but are very dangerous for construction of roads, air strips, buildings, laying gas, water pipelines which get distorted, develop cracks and lead to sunken floors etc.

Soil Classification

Soil classification deals with the systematic categorization of soils based on distinguishing characteristics as well as criteria that dictate choices in use.

Soil classification is grouping of objects in orderly and logical manner into classes based on the properties of soils (differentiating characters) for the purpose of studying and identifying them. The soil individuals are grouped into classes of the lower category (soil series) which are grouped into classes of higher categories (soil orders). The lower categories are defined by large number of differentiating characters and higher category by a few differentiating characteristics.

For soil resources, experience has shown that a natural system approach to classification, i.e. grouping soils by their intrinsic property (soil morphology), behaviour, or genesis, results in classes that can be interpreted for many diverse uses. Differing concepts of pedogenesis and differences in the significance of morphological features to various land uses can affect the classification approach. Despite these differences, in a well-constructed system, classification criteria group similar concepts so that interpretations do not vary widely. This is in contrast to a technical system approach to soil classification, where soils are grouped according to their fitness for a specific use and their edaphic characteristics.

Soil survey is essentially a study and mapping of soils in their natural environment. It is the systematic examination, description, classification and mapping of soils of an area.

2.1. History of Soil Survey in India

The original investigations on Indian soils were carried out by Voelcker dates back to 1893 and by Leather to 1898.They classified the soils of the country into four major groups, namely the Indo-Gangetic alluvium, the black cotton soil or regur, red soil and laterite soil. Schokalskaya (1932) has published a soil map of India based on the Russian concept which describes 16 soil groups such as climate,vegetation, soil-forming materials, salinity, alkalinity, swamps and peats (Bhattacharyya et al. 2013). In 1935,Wadia and his co-workers collected a soil map of India with significance on geological formations and classified the soils as red, black (regur), laterite and lateritic soils of Peninsular India and also Indo-Gangetic Plains (IGP) which includes delta, desert, bhabar, terai and alkali soils. Vishwanath and Ukil (1943) published a soil map of India by placing the soils in different climatic zones for the first time. This was prepared by Imperial Agricultural Research Institute, New Delhi, and published in the year 1943. There were 17 kinds of soils identified, viz., deep black soils, black clay soils, black loamy soils, black sandy soils, red sandy soils, brown sandy soils, red and yellow soils, dark reddish brown soils, mixed soils (white and yellow), alluvium (Indus, Gangetic, Brahmaputra), coarse alluvium, soils of swamp lands, calcareous soils, usar soils, kallar soils, coastal alluvium soils and soils of Great Himalayan Ranges.

Soil survey works were started in 1954, in most of the states as a part of their agricultural development programme, and Bihar (Soil Survey and Land use Planning Scheme, Sabour) was pioneer. In 1954, the soil survey work was started under the leadership of Dr. P. P. Jha following the conventional procedures in Bihar (including Jharkhand) to delineate the soil associations based on geology, relief, physical and chemical characteristics of soils for the first time in India by the then Soil Survey Scheme at Sabour (Mishra et al. 2001; Mishra 2015, 2016). Meanwhile, the National Atlas Organization, Kolkata, prepared a soil map of India in 1957 classifying Indian soils into six major groups and 11 broad types. Murthy and Pandey (1983) applied the working principles of the USDA 7^th Approximation in classifying the Indian soils with available data on soil classes and thus used the US system for the first time at great soil group level, which was transformed into a soil map of India on 1:6.3 million scale. Mishra et al. (1994) attempted to propose “Fluvisols” as the 13th Order in USDA Soil Taxonomy for active floodplain soils frequently occurring in different parts of India and elsewhere. Mishra (2015, 2016) proposed a framework of Indian system of soil classification mainly based on land use options.

1.1. Soil Resource Evaluation

Soil is the essence of life on the planet Earth. It has sustained humanity and human civilizations through five functions (Karlen et al. 1997) viz., i) sustaining biological activity, diversity and productivity; ii) regulating and partitioning water and solute flow; iii) filtering, buffering, degrading, immobilizing and detoxifying organic and inorganic materials, including industrial and municipal byproducts and atmospheric decomposition; iv) storing and cycling nutrients and other elements within the earth’s biosphere; and v) providing support to socioeconomic structures and protection for archaeological treasures associated with human habitation. Reeling under the pressure of increasing food, fodder, feed, fibre and fuel production, soil has been used as a medium of plant growth with considerable reliance on external supply of major nutrients, irrigation water, plant protection chemicals, etc. Although soil, a product of millions of years of weathering, has supported various forms of terrestrial life, its sustainable management holds the key for meeting the basic requirements of burgeoning population and development commitments. So intense has been the pressure of increasing food, fodder, feed, fibre and fuel production that the soil has been exploited often exceeding its carrying capacity. The soils are increasingly used for agricultural and non-agricultural uses, such as disposal of farm, urban and industrial wastes, ensuring environmental safety etc. This is possible by the judicious use of this resource.

A clear and intimate knowledge of the kinds of soils and their extent of distribution are essential prerequisites in developing rational land use plans for agriculture, forestry, irrigation, drainage, etc. soil resource inventory or mapping provides an insight about their potentials and limitations. It is therefore imperative to prepare an inventory of this resource for developing optimum land use plan and conservation plans.

Abstract

GIS has several products that can be protected in India as copyright. The paper describes major provisions of copyright Act, 1957 that has been amended five times. GIS products qualify to be registered within various sections of the copyright Act. Patenting of software is permitted in some countries but not in India, a comparative account of these two forms of protection has been discussed with practical examples. General public licensing of open source software, translation, exclusive licensing and data sharing & accessibility policy are other areas covered in the present study and analytical learning.

Key words : copyright, patent, GIS, software, data sharing

1.0 Introduction

The copyright Act 1957 was mainly amended in 1994 and1999 to bring into complete harmony with Trade Related Aspects of Intellectual Property Rights (TRIPs), further major amendment has been done in 2012, that include wide range changes in ownership, term of protection, copyright security, cinematography and broadcasting provisions. In the same year government of India has initiated ‘National Data Sharing and Accessibility Policy (NDSAP)’ which came into operation from February 2012. At present the copyright Act and data sharing policy are the two legal and administrative instruments which facilitate the intellectual property protection and appropriate sharing among stakeholders in the country.

Abstract

Any naturally occurring phenomena varies both in space and time. This variability is a result of various natural process and hence deterministic. Geostatistics is a tool to help us to characterize spatial variability and uncertainty resulting from imperfect characterization of the variability. Geostatistics involves the theory of regionalized variables, which dates back to the early fifties and includes concepts of random function and stationarity. Geostatistical mapping can be defined as analytical production of maps by using field observations, explanatory information, and a computer program that calculates values at locations of interest. There area number of spatial prediction models depending on the amount of statisticsinvolved in the analysis. Kriging is a generic name adopted by the geostatisticians for a family of generalized least- squares regression algorithms and various kriging algorithms viz., punctual kriging, block kriging, co-kriging and universal kriging are explained in this paper. Applications of geostatistics can be found in many varied disciplines ranging from the geology to soil science, hydrology, meteorology, environmental sciences, agriculture and even structural engineering and some of its applications are summarized in this paper.

Keywords :Geostatistics, spatial variability, kriging, model

Abstract

GIS in marine fisheries has taken off much later than its application in land. But the strides made in this field since 1990’s has been quite significant, as many serious mapping studies and modeling initiatives have been recorded. With the third dimension added to the 2D spatial data, the marine GIS have all the ingredients of making it a fertile domain for research for decades to come. Most of the studies and products pertaining to GIS in fishery management had been revolving around mapping of habitats, geo-referencing of catch and effort data and modeling linking oceanographic and biogeochemical factors with living resources. Satellite remotely sensed information like ocean colour can act as a surrogate to fish biomass. Further remotely sensed SST, wind and other parameters can be effectively modeled to predict fish abundance, their habitat and related aspects. This manuscript pours into the various products and outputs based on GIS in marine fisheries around the world and the Indian initiatives.

Key words: GIS, marine resources, oceanography, primary productivity and climate change

1.0 Introduction

Geographic Information Systems (GIS) have been one of the most prolific scientific enhancements in recent past, which by virtue of out of box expansion of traditional database concept have opened up an entirely new vista of knowledge and opportunities. It’s probably one such unique application where information collation and analysis happen hand in hand resulting in palpable mining of data in perspective. A formal introduction to GIS would define it as a collection of computer hardware, software, data and personnel designed to collect, store, update, manipulate, analyze and display geographically referenced information. By virtue of its conceptualizations, there are no single GIS; systems can be assembled in an infinite number of ways. This is one such field, which probably always seeks the frontiers of innovations in the fields of ICT and modeling.

Abstract

The objective of the study is to build a framework of Geo-spatial Information System for effective decision making by empowering all the stake holders with spatial and non-spatial data. The Interface of this information system is developed as a deployable windows application using Map Objects in Visual Basic programming language with MS Access database. The practical utility of the proposed information system was explained with a case study in Aquaculture. This geo-spatial information system provides required information through maps based on spatial and attribute quarries. These dynamic maps help in taking effective decisions.

1.0 Introduction

Computer based information systems proved to be very efficient and effective tools for managing data and information to aid in decision making . FAO (2000) proposed agricultural knowledge and information system for rural development (AKIS/RD) to link rural people and institutions to promote mutual learning and generate , share and utilize agricultural technology , knowledge and information. This serves as vehicle for sharing ideas and principles with various stake holders addressing the problems and seeking solutions to rural development. Although the rural development planning is top-down prescriptive approach , in reality the decisions are made by the stake holders based on their perspectives, knowledge and priorities. Problems particularly related to environmental impacts are location specific and contextual. Geo-spatial technologies may serve as better vehicle to store and share all kinds of location specific data and information. The state of mapping and management of geospatial data changed during the recent years with the diffusion of modern geospatial information technologies such as GIS(Geographic information system), GPS(Global positioning system) and image analytical system for remote sensing(RS) data. Adinarayana et al., (2008) proposed a geographical information and communication technology (Geo-ICT) based information system called Grama Vikas( rural development) to assist the user in analyzing the rural information for rural development, planning . During the recent years there is a paradigm shift in GIS applications for rural development particularly in developing countries, by way of integrating top-down approach with bottom-up approach by the stake holders who stand to be affected by the decisions based on these technologies. Emerging concepts include “ community - integrated GIS”, “GIS in participatory research” and ‘participatory GIS”. (Abbot et al., 1998)

Abstract

The social and economic development of any state is interlaced with the manner of its natural resource management. The unplanned use and overexploitation of resources are results in various kinds of land degradation, biomass deterioration and siltation of tanks. In addition, the low per capita availability of land, erratic and uneven distribution of rains, undulating topography, improper management, traditional cropping programmes and recurrence of droughts having cumulative effect leading to low productivity and high risk particularly in dryland farming. Further, developing dry land agriculture through sectoral approach did not bring in the desired results, as the efforts were not integrated. However, in nature all the resources are inter-linked and thus, the integrated developmental approach is the best solution for optimal development of any area. Further, development based on administrative units such as district, taluk, block and village have resulted in imbalance and sometimes, no overall development in some areas. Considering this, natural resources management through Geo- informatics tools like, remote sensing, GIS, GPS and other sensor based techniques are the possible ways for making agriculture sustainable. The paper mainly highlights theimportance of application of latest technologies in agriculture along with some field level case studies.

Keywords: Remote sensing, GIS, Watershed, CAPE, Precision agriculture

Abstract

A huge technical improvement in Information Technology (IT) has made new instruments (e.g. WEB-GIS, Open Source platforms, DBMS with geometric data) available. Distributing geospatial information on the Internet is an enforcing factor for information providers. For dissemination of spatial data, Web-GIS technology can be used, which is amalgamation of several information technologies. Open Source is a philosophy of providing software with better quality, more flexibility, and lower cost. This paper explains the use of Open Source Web-GIS which provides a fast and globally reachable way not only to represent the information about natural resources through maps and statistics but also possibility of processing the information interactively on web.

Keywords : Web-GIS, Open Source, PostgreSQL, PostGIS, GeoServer, Wetlands

1.0 Introduction

India is blessed with diverse and abundant resources. India has been witnessing tremendous growth which has impacted practically every aspect of environment and the common man. Natural resource has been tremendously in use due to increase in population growth, thus generation, dissemination and sharing of information regarding natural resources and data amongst all stake holders have become a necessity. The utilization of modern technologies such as remote sensing, GIS which are effective in management of natural resources as user can store, retrieve and model the spatial information. Web media is playing a vital role in making people aware about the importance and conservation of natural resources. We are presenting such efforts with use of Free and Open Source Software (FOSS) tools.

Abstract

Customized application development can deliver/fulfill the specialized and specific needs of the users as well as it provides user- friendly environment to the users. There have been applications developed in the past but now applications developed and coupled with the advantage of GIS technologies for various data-handling, spatial analyses and visualization under variable inputs and spatial scales is an innovative approach developed during recent years.The present work encompasses Spatial Agricultural Information and Decision Support System having five modules - Agro-socio-economic-information, Bio- Physical Information, Crop’s Information & Management, and Agriculture DSS Module. This system, developed in a GIS framework, allows managers and planners to rapidly assess land attributes and link these attributes with maps and related infrastructure. Hence, it can facilitate efficient use of existing resource information. The primary database of the software has a Database Update feature which can be utilized by the user using the software to integrate own data into the primary database of the software. With this integration, the software adapts to new data entered and will enable this data to be visualized in GIS platform. The software has been designed keeping in view the requirements of the departments like Department of Agriculture, Department of Land Records etc. In comparison with the commercial GIS applications, the commercial applications are not cost effective if the primary requirement is visualization enabling decision making and basic spatial analysis. The most features available on such software remain un-utilized or they cannot be used without having GIS knowledge. This application is suitable in such scenarios, providing a simple customizable platform for GIS visualization. This software application fits in and serves the line departments and in a way promoting the GIS in the mountainous terrain as it requires very basic or no GIS skill set to operate.

Abstract

Natural resources and agricultural production processes vary spatially. Capturing the spatial variations in data and knowledge of natural resources and production processes has been a major challenge for efficient and sustainable management of agricultural production systems. Geographical Information Systems (GIS) provide an effective platform for storing and mapping spatial data and modeling the relevant processes. Huge volumes of geospatial data on specific themes such as soils, water, climate, and other natural resources, are being collected by public and private agencies. However, currently it is difficult for most users to access the data and integrate them into a GIS platform to derive useful information and knowledge for specific applications. There is a need to create geospatial data and knowledge systems that can provide efficient, on-demand and remote access of spatial data to users to enable development of a variety of GIS applications for agricultural and natural resources management. The design of a prototype geospatial library to provide web-based access to geospatial data, services, and learning and knowledge resources that can support agricultural and natural resources management is presented. The design is scalable and sufficiently general to allow a range of agricultural and natural resources management applications across different spatial scales.

Keywords: Agriculture, GIS, Geospatial library, Knowledge Management, Natural Resources

Abstract

The weather or climate is a natural resource and is an important basic input in agricultural planning and strategies. Every plant process, related with growth, development and yield of a crop and each of inseason and off-season farm operations (according to World Meteorological Organization) is more than 10 per cent and can reach up to 50 per cent in smaller areas and not a surprise even if it reaches to 100 per cent on micro scale. Amongst the various weather elements, temperatures, radiation and rainfall play major role in deciding the crop growth and yield levels. Precipitation is one of the important weather factors being responsible for atmospheric and soil moisture and therefore has more agricultural importance, especially in rainfed agriculture.

Keywords: Remote sensing, weather, agroadvisory, GIS

1.0 Introduction

India receives more than 70 per cent of its annual rainfall during South West monsoon season. Indian summer monsoon rainfall shows large intra - seasonal and intra-annual variability (Parthasarathy, 1960; Alexander et al., 1978; Mooley and Parthasarathy, 1984) and also changes in space and time, intensity and distribution. Borgaonkar and Pant (2001) have reported that Indian monsoon rainfall has shown trend less nature since 17^th century based on proxy data with large inter-annual fluctuations. IPCC (2001) has reported increase in rainfall over tropical and higher latitudes and decrease in rainfall over subtropics and mid latitudes.

Abstract

Anantapur is the driest district of Andhra Pradesh and hence, agriculture conditions are very often precarious. Groundnut grows where other crops fail and thus it is the predominant crop of Anantapur district. Groundnut is grown in about 7.5 lakh ha in Anantapur district; however the average yields are low at 500 kg ha^-1. Among various available vegetation indices, normalised difference vegetation index (NDVI) is widely used for all reasons, which is a single numerical indicator of presence and condition of green vegetation. NDVI mapping at a regional scale helps to assess the spatial changes in the vigour of green vegetation and thus occurrence of any moisture stress. Climate tools have a great role in understanding the crop performance and estimating the yields. This study was taken up by using freely available MODIS data to understand NDVI in terms of abiotic stresses over Anantapur district and linking with the actual rainfall conditions, groundnut crop acreage and production. Results indicate that low groundnut yields in general could be related to NDVI-based stress measurements and rainfall quantum and distribution in the area however, with a few exceptions. It is hoped that by combining improved practices through IWM with climate-adapted crop varieties, rainfed farmers of Anantapur district can sustain their crop production under present climate variability and become resilient to future climate change.

Keywords: Climate, MODIS, NDVI, Anantapur, Groundnut, Integrated Watershed Management

Abstract

Higher temperature and altered rainfall patterns accompanied by extreme weather events are being considered indications of climate change. These factors impact vegetation growth in natural forest, open scrub and in agriculture land. Vegetation index based on satellite data was used to analyse agricultural vulnerability in India to understand impact of rainfall variability. Time-series Normalized Difference Vegetation Index (NDVI) data products obtained from AVHRR (1982 to 2006) and MODIS (2000-2011) were analyzed to assess spatial and temporal variability. Coefficient of variation of maximum NDVI was assessed for the study period and results were corroborated with Standard Precipitation Index (SPI) instead of actual rainfall. Resolution of AVHRR time-series data facilitated study at regional-scale while MODIS datasets with 250m pixel resolution helped in identifying vulnerability at district-level. Study indicated that over 241 Mha areas in the country may not be vulnerable to rainfall variability induced climate change while over 81.3 Mha in arid, semi-arid and dry sub- humid regions may be vulnerable. Study indicated that over 12.1 and 1.81 Mha of Kharif cropland would be mildly and severally vulnerable while 6.86 and 0.5 Mha of Rabi cropland may be adversely affected in a similar manner. Study indicated that length of cropping season was decreasing due to delay in start of season. The paper also presents analysis of variations in SPI and resultant NDVI in typical drought and flood years in the country.

Keywords: MODIS, AVHRR, NDVI, Rainf ed Agricul ture, Vulnerability, Climate Change

Abstract

This study was conducted at Directorate of Cashew Research (DCR) Puttur, D.K., Karnataka during 2007-12. In this study, a methodology was standardized to find the area under cashew, barren areas and other areas for expanding cashew cultivation with remote sensing. It was found that the images pertaining to the month of November was best for classifying cashew since the colour of cashew leaves changes during that period. Also, the LISS III images were found to be good for identifying cashew. It was not possible to differentiate between cashew seedling area and cashew graft area using LISS III or LISS IV images. A spatial database of soil moisture was prepared for the irrigation scheduling in cashew and a spatial database of major nutrients was prepared for the site specific nutrient management in cashew gardens. A spatial database of land slope and stream orders was prepared using GIS and suitable soil and water conservation interventions were suggested for the selected area.

Keywords: Cashew, GIS, remote sensing

Abstract

The sustainable management of plant genetic resources is of great concern as increasing population and rapid technological strides are putting enormous pressure on this country’s nutritional and food security. Management of plant genetic resources at national level generates and uses enormous data and analysis of these data is crucial to the effectiveness of PGR management process and can add significantly to the value of genetic resources. A GIS is a database management system that can simultaneously handle data representing spatial objects and their attribute data. GIS allows us to view, understand, question, interpret, and visualize data in many ways that reveal relationships, patterns, and trends in the form of maps, globes, reports, and charts. It can play an important role in the management of large and complex PGR datasets. The article analyses the potential uses of GIS in plant genetic resources management in India covering various activities such as germplasm exploration and collection, characterization and evaluation, plant health management, documentation and conservation.

Key words : plant genetic resources, germplasm, conservation, documentation, DIVA-GIS,

Abstract

Geographical Information Systems (GIS) application in plant genetic resource management allow capture, manipulate, process and display of georeferenced data integrated with genetic resource database for operations such as query and statistical analysis, visualization and geographic representation. GIS based several spatial tools have been developed that model species’ ecological niches finding a relationship between crop or variety with a set of environmental parameters and useful for planning exploration, evaluation trials, in situ and ex situ conservation sites. GIS technologies have direct practical application in elucidation of genetic, ecological and geographic patterns in the distribution of crops and wild relatives; mapping of richness, diversity, distribution of useful traits and, location of areas with complementary diversity; gene bank information management and strategies for future explorations and gap analysis; selection of suitable accessions/sites for ex situ evaluation; searching germplasm for abiotic stress tolerance and developing core collections. With the increasing availability of high- speed computers and software development in the area of GIS tools specific to PGR management increasing trend in application of these is expected. Apart from ecogeographic survey for locating diversity and germplasm collection and design, management and monitoring of in situ reserves, introduction of new varieties, and development of core collection, locating gene donors for biotic and abiotic stresses are the areas to be benefited with the GIS application.

Keywords: GIS, genetic resource, distribution, diversity, core collection, gap analysis, mapping

Abstract

Agroforestry is an integrated self-sustainable land use management system that is not only capable of producing food from marginal agricultural land but also capable of maintaining and improving the quality of environment. It plays a vital role in achieving integrated rural and urban development. But reliable data on number of trees and area under agroforestry is not available as methodology for estimation of even area under agroforestry is not yet standardized. In this paper, a methodology for estimation of number of trees under agroforestry using high resolution satellite data has been proposed and estimation of number of trees as well as area under agroforestry in Ludhiana district of Punjab State has been done using the proposed methodology. Land use/land cover map of the district has also been generated using ERDAS IMAGINE software. It has been observed from the accuracy assessment that the estimates of number of trees as well as area under agroforestry obtained using the proposed methodology under this study are very reliable. Therefore, the proposed methodology may be replicated for estimating number of trees as well as area under agroforestry in other parts of the country.

Keywords: Agroforestry; Estimation of number of trees, Area estimation; Remote Sensing; GIS

Abstract

Agroforestry is an ancient practice that farmers have adopted throughout the world. There are innumerable examples of traditional land use practices combining production of trees and agriculture crops on the same piece of land. In India, the organized agroforestry research began in 1979 when a Seminar on Agroforestry was organized at Imphal by the ICAR, New Delhi. As a follow up to this, ICAR launched an All India Co-ordinated Research Project on Agroforestry (AICRPAF) was started in 1983. The diagnostic survey and appraisal revealed that there are enumerable agroforestry practices prevalent in different agro- ecological zones of India occupying sizeable areas. However, spatial technologies like Geographical Information System (GIS), Remote Sensing (RS) and Geographical Positioning System (GPS) have yet to be implemented extensively in this field in India. The spatial technologies have shown great potential in natural resource management through out the world, especially in developed countries in the fields like forest cover mapping, agricultural planning, watershed management, land use planning, etc. In India the agroforestry land use occupy large areas but use of these technologies to estimate area has been initiated in year 2007 with DST sponsored project entitled ‘Spatial and Temporal analysis of agroforestry interventions in North-western India using GIS and Remote Sensing’ The area under agroforestry systems has been estimated/ mapped in two districts viz., Yamunanagar (Haryana) and Saharanpur (Uttar Pradesh), where intensive commercial agroforestry was predominant. Besides, the methodology developed as an out come of this study may be replicated for agroforestry systems existing in other parts of the country.

Keywords: Agroforestry, Geo-spatial, Mapping, Natural Resources, Remote Sensing.

Abstract

Remote sensing and Geographic Information System (GIS) are integrated system in providing precise information on nature, extent and spatial distribution of land resources to assess their potential and limitations for planning, monitoring and management towards sustainable development. The use of remote sensing and GIS provide immense opportunities in the field of large-scale mapping, generate and update of existing geographical databases for decision making in site- specific management and development of land resources. Integration of remote sensing and GIS includes the use of each technology to benefit the other, as well as the application of both the technologies for geospatial modelling and decision support. Remote sensing and GIS integration has clearly benefited from advances in computing and Global Positioning System (GPS) technologies, including innovations in use of decision tree algorithms and neural networks. The generated precise spatial database in GIS on land resources, socio-economic and contemporary technologies could be effectively used to develop GIS based Spatial Decision Support Systems (SDSS) for sustainable management of land resources. In this article an attempt has been made to provide an overview on the remote sensing and GIS technologies as a special decision support tools in inventory, characterization and management of land resources particularly in digital terrain analysis, geomorphological mapping, hydrological applications, soil resource inventory, assessment of soil loss, land degradation and soil fertility, soil-site suitability and watershed prioritization.

Abstract

Soil quality assessment has been recognized as an important step towards understanding the long term effects of land management practices within agricultural watersheds. Potential soil quality issues include continued high rates of erosion, losses of organic matter, reductions in soil fertility and productivity, as well as chemical and heavy metal contamination. This case study addressed the spatial variability of soil properties and its quality at the watershed level using geostatistical methods. Soil samples from the 0- to 20-cm depth were collected on a 100- by 100-m grid across an 88-ha watershed at Sakaliseripalli village in the Nalgonda District in Andhra Pradesh State, India. Geostatistical analysis showed that most of the soil parameters were moderately spatially dependent. An assessment framework, that included a minimum data set, linear scoring technique, and additive indices, was used to evaluate the soil quality index (SQI). Through principal component analysis, cation exchange capacity, exchangeable Na percentage, DTPA-extractable Zn, available P, available water, and dehydrogenase activity have been emerged as the most important indicators for evaluating soil quality. A kriged map of SQI was prepared for the watershed. The SQI was found to be higher in irrigated systems than under rainfed conditions. In the study, potential soil loss calculated using the Universal Soil Loss Equation and crop yield were identified as the quantifiable management goals; the results indicated that soils having higher soil quality indices were more productive and less erosion prone.

Keyword : Principal Component analysis, SQI, Watershed, Geostatistics, Potential soil loss

Abstract

Runoff from rainfall is an important component of the hydrological cycle. Estimation of runoff is critical for the design of hydrological structures and drainage systems in watersheds. Different soils, land use, and water management practices affect runoff differently. In real watersheds, land use, soils and weather conditions vary spatially over the geographical area of the watershed leading to spatial variations in runoff. Also, most watersheds form a part of larger drainage basin or a large watershed consisting of several such subwatersheds. Each subwatershed is hydrologically connected to the other subwatersheds of the basin. A comprehensive GIS based decision support system (DSS) for estimation of runoff that includes the spatial variations in rainfall and natural resources is presented. The DSS is developed as a deployable application by integrating independent GIS layers of watershed features created in ArcGIS with MapObjects in VB, for a case study watershed - the KK3 watershed in Mahbubnagar district of Andhra Pradesh, India. The DSS generates thematic maps of spatial variations in runoff on individual rainy days for the subwatersheds.

Keywords : GIS, GUI, Land use, Rainfall, Remote Sensing, Runoff, Soil, Sub-watershed, Watershed 228 Geospatial Technologies for Natural Resources Management

Abstract

Remotely sensed data have become the primary realistic source for natural resources and biomass estimation, since last 30 decades. A summary of earlier research on remote sensing and GIS based biomass estimation approaches and a discussion of existing issues prompting biomass estimation are very valuable for further improving biomass estimation performance with the integration of geographical information systems. This paper discusses the recently most accurately alternative research methods to integration of remote sensing and GIS applications for identification, characterization and analysis of biophysical characters. The remote sensed data and geographical information systems using the accurate assessment of natural resource and management for the enhancement of biomass production and estimation. There is not any other option for the perfectly biophysical and natural resources estimation in small to large area. The earlier research has demonstrated that biomass estimation remains a challenging task, especially in those study areas with complex forest and mixed traditional cropping systems and environmental conditions. Either optical sensor data or radar data are more suitable for forest sites with relatively simple forest stand structure than the sites with complex biophysical environments. A combination of spectral responses and image textures improves biomass estimation performance. More research expertise is needed to focus on the integration of remote sensing, GIS& GPS, the use of multisource data, and the selection of suitable variables and algorithms for biomass estimation at different scales. Understanding and identifying major uncertainties caused by different stages of the biomass estimation technique and applying strength of mind to reduce these uncertainties are critical.

Keywords : Integrating, Remote Sensing, Bio-physical, Resources, Environment

Abstract

Any country’s socio-economic development essentially depends on land and water resources. Resource depletion takes place when there is an overstretching due the exploding population, calling for prudent management of the resources. Application of remote sensing and Geographical Information System (GIS) tools in the management of natural resources at different levels including watersheds is quite well known. In addition, applied geoinformatics are also used in research on management of these delicate resources also besides characterization. There is a continuous advent in technology in both hardware and software necessitating updation of application scientist/manager. Once an exclusive tool of elite institutions and government agencies, GISnow became an indispensible part of our day-to-day life. As the urge for information intensifies, new applications of GIS continue to evolve. A concerted effort is needed to develop an information system when vast expanses of natural resources are to be managed and a combination of information tools like remote sensing, global positioning system and GIS always updates the database effectively. However, the cost factor should not hinder the applications at micro level. This necessity calls for attention to popularize free and open sources of software (FOSS) and data (particularly digital elevation models (DEM) and satellite imagery) to put the techniques into use by enthusiasts at village level such that a database at a regional level can be built through participatory GIS. It is in this direc tion the av ailab le li terat ure on appl ied geoinformatics coupled with use of FOSS is reviewed and presented in this article to give an idea as to how an open ended information system could be developed to help the management.

Keywords: Natural resources, management, Remote sensing, GIS, FOSS, DEM