Engr.

PRECISION FARMING

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1.0 SCOPE AND NATURE OF PRECISION FARMING
Let??™s say you are a commercial rice farmer working on a 15,000ha of land at Adani, Enugu state early in the growing season with a limited number of staffs of about 20 persons comprising of 40% engineers and technicians to take care of machine repair and maintenance,60% unskilled labourers??™ for miscellaneous chores.
As the manager, you drove to the office this morning, turn on you geographical information system which displays an aerial view of your farm giving you an option to zoom into any part of the farm land within a reasonable length. Also, updated information collected on your field just yesterday by the various sensors and transferred through the global positioning system (GPS) to the base Centre are been displayed on a section of the screen. You punch a button which displays a yield map (YM) of your farm showing the variations in yield across the farm land and where the soil loses nutrients over the season, all this information s collected by a device called ???the yield monitor??™ . Punching another button, a list of information is displayed on your screen showing where there are pest and disease attack and the gravity of the infections. Gathering this information and with the help of a mapping software, you develop an algorithm on how the day??™s activities will be carried out. Having uploaded the information on the data base to regulate the application of resources in specific amounts using the variable rate technology (VRT), you ???hit send??™ to transfer the information through the GPS to the field monitoring systems. You sit back and enjoy the ride saving both cost and time as the machines do most of the job in precise formats as have been stipulated by you. Haven achieved all this, then I must say ???congratulations??™, you are among a new generation of growers called ???precision farmers??™.
Precision farming relies upon intensive sensing of environmental conditions and computer processing of the resulting data to inform decision-making and control farm machinery. Precision farming technologies typically connect global positioning systems (GPS) with satellite imaging of fields to remotely sense crop pests or evidence of drought, and then automatically adjust levels of irrigation or pesticide applications as the tractor moves around the field. Yield monitors fitted to combine harvesters measure the amount and moisture levels of grains as they are harvested on different parts of a field, generating computer models that will guide decisions about application or timing of inputs.
Precision agriculture promises higher yields and lower input costs by streamlining agricultural management and thereby reducing waste and labour costs. It also offers the potential to employ less skilled, and therefore cheaper, farm machinery operators since, theoretically, such systems can simplify and centralize decision-making. In the future, precision farming will resemble robotic farming as farm machinery is designed to operate autonomously, continuously adapting to incoming data.
Precision Farming (PF) concept is spreading rapidly in developed countries as a tool to fight the challenge of agricultural sustainability. With the progress and application of information technology in agriculture, PF has been increasingly gaining attentions worldwide. Huge work has been started in different corners of the world on this subject. Knowledge on present developments helps to foresee the forthcoming challenges. Hence, this research work provides an overview of development and current status of precision agriculture in Nigeria, if there is, if there can be, the possible challenges and propose prospects.

1.1.0 DEFINITION OF BASIC TERMINOLOGIES

1.1.1 PRECISION AGRICULTURE/PRECISION FARMING:
Precision agriculture can be defined as the application of various information and communication technology (e.g. satellite, GPS, GIS, sensors, electronic/ communication, computer, aerial photograph equipment, etc ) in measuring and analyzing variations within agricultural field or animals; and applying the knowledge gaining in the management and control of soil , water, farm inputs, micro climate, environment, machines and machine related parameters for optimum production of crop and animals (Engr. A.O. Ani 2010)
Over the years, as a result of the illiteracy on the part of people in the third world??™s nations, there has been a misconception on the difference between ???agriculture and farming??™. According to Encarta encyclopedia, Agriculture: farming, is the occupation, business, or science of cultivating the land, producing crops, and raising livestock.
Some say farming refers to the growing of crops while agriculture is a general name for all farm activities including the cultivation of land for the growing of crops and rearing of animals. The misconception was due to the use of other unexplained (which were misunderstood by the uneducated individuals) agricultural terminologies like fishery, processing, and deforestation etcetera.
Precision Agriculture is the application of technologies and principles to manage spatial and temporal variability associated with all aspects of agricultural production for improving production and environmental quality. The success in precision agriculture depends on the accurate assessment of the variability, its management and evaluation in space-time distribution in crop production. The agronomic success of precision agriculture has been quite convincing in crops like sugar beet, sugarcane, tea and coffee. The potential for economic, environmental and social benefits of precision agriculture is largely unrealized because the space-time distribution of crop production has not been adequately addressed. Precision agriculture is a relatively new area that combines the latest in geographic technology with cropping situations to optimize inputs, reduce waste, and generate the maximum possible yields. The technology often involves the use of GPS and remote sensing for data collection, GIS for data processing and analysis, and variable rate technology for implementing ideal models.

1.1.2 NATURAL RESOURCES VARIABILITY:
Soil and landscape variability, digital elevation models, soil mapping, geostatistics, geographic information systems, microclimate, weather forecasting, remote sensing, management units, scale, etc.
1.1.3 MANAGING VARIABILITY:
Sampling techniques, site-specific nutrient and crop protection chemical recommendation, crop quality, tillage, seed density, seed variety, yield mapping, remote sensing, record keeping systems, data interpretation and use, crops (corn, wheat, sugar beets, potatoes, peanut, cotton, vegetables, etc.), management scale, etc.

1.1.4 ENGINEERING TECHNOLOGY:
Computers, positioning systems, DGPS, machinery, tillage, planting, nutrient and crop protection implements, manure, irrigation, fustigation, yield monitor and mapping, soil physical and chemical characteristic sensors, weed/pest mapping, etc.

1.1.5 PROFITABILITY:
MEY, net returns, BMPs, optimum recommendations, crop quality, technology cost, sustainability, social impacts, marketing, cooperatives, farm scale, crop type, etc.

1.1.6 ENVIRONMENT:
Nutrient, crop protection chemicals, sediments, leaching, runoff, practices, field, watershed, on/off farm, artificial drainage, ground water, surface water, etc.

1.1.7 TECHNOLOGY TRANSFER:
Skill needs, education, training, outreach, methods, surveys, agri-business, producers, distance education, Internet, simulations models, decision support systems, expert systems, on-farm experimentation, partnerships, quality of rural life, etc.
1.1.8 YIELD FORECASTING:
Plant tissue absorbs much of the red light band and is very reflective of energy in near infrared (“NIR”) wavebands. The ratio of these two bands is referred to as the vegetation index (“VI”). The difference of red and NIR measurements divided by their sum is normalized difference VI (“NDVI”).
For crops such as grain sorghum, production yields, leaf area index (“LAI”), crop height and biomass have been correlated with NDVI data obtained from multispectral images (Anderson et al, 1996). In order to get reasonably accurate yield predictions this data must be combined with input from weather models during the growing season (Moran et al, 1997).
1.1.9 MANAGEMENT DECISION SUPPORT SYSTEMS:
Just having information about variability within the field doesnt solve any problems unless there is some kind of decision support system (“DSS”) in order to make VRT recommendations. Russo and Dantinne (Russo et al, 1997) have suggested the following steps for a DSS:
1. Identify environmental and biological states and processes in the field that can be monitored and manipulated for the betterment of crop production.
2. Choose sensors and supporting equipment to record data on these states and processes.
3. Collect, store and communicate the field-recorded data.
4. Process and manipulate the data into useful information and knowledge.
5. Present the information and knowledge in a form that can be interpreted to make decisions.
Choose an action associated with a decision to change the identified state or process in a way that makes it more favorable to profitable crop production.

1.1.10 WHO IS FARMERS EDGE
Farmers Edge offers a complete land management solution regardless if you are a 2000ac producer or a large corporate farm.
? From project development to crop planning to operations and harvest management, Farmers Edge is dedicated to improving farmers land management practice by providing growers with solutions that increases their profits.
Our land management solutions and services include advanced agronomy ??“ a balance of traditional agronomy and new technology, soils analysis, carbon aggregation, traceability and in-season crop monitoring and record keeping.

1.2.0 PRECISION FARMING TECHNOLOGIES
Precision farming basically depends on measurement and understanding of variability, the main components of precision farming system must address the variability. Precision farming technology enabled, information based and decision focused, the components include,(the enabling technologies) Remote Sensing (RS), Geographical Information System (GIS), Global Positioning System (GPS), Soil Testing, Yield Monitors and Variable Rate Technology. Precision farming requires the requisition, management, analysis and output of large amount of spatial and temporal data. Mobile computing systems were needed to function on the go in farming operations because desktop systems in the farm office were not sufficient. Because precision farming is concerned with spatial and temporal variability and it is information based and decision focused. It is the spatial analysis capabilities of GIS that enable precision agriculture. GPS, DGPS has greatly enabled precision farming and of great importance to precision farming, particularly for guidance and digital evaluation modeling position accuracies at the centimeter level are possible in DGPS receivers.
Precision farming technology (PF) is designed to provide data and information to assist farmers when making site-specific management decisions. By making more informed management decisions, farmers can become more efficient, and perhaps lower costs, and become more profitable. However, little is known about how farmers use PF to make management decisions, identify production problems, and about the relative magnitude of benefits and costs of PF on individual farms.
1.2.1 The global positioning system;
The global positioning system (“GPS”) is a network of satellites developed for and managed by the U.S. Defense Department. The GPS constellation of 24 satellites orbiting the earth, transmit precise satellite time and location information to ground receivers. The ground receiving units are able to receive this location information from several satellites at a time for use in calculating a triangulation fix thus determining the exact location of the receiver.
1.2.2 Geographical information system;
A geographical information system (“GIS”) consists of a computer software data base system used to input, store, retrieve, analyze, and display, in map like form, spatially referenced geographical information.

Fig fig.1. A GIS chart showing the network link

1.2.3 Yield monitors;
Yield monitors are crop yield measuring devices installed on harvesting equipment. The yield data from the monitor is recorded and stored at regular intervals along with positional data received from the GPS unit. GIS software takes the yield data and produces yield maps.
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Fig.2. a representation of a yield map on a GIS system

1.2.4 VARIABLE RATE TECHNOLOGY;
Variable rate technology (“VRT”) consists of farm field equipment with the ability to precisely control the rate of application of crop inputs and tillage operations.

Precision farming technologies have been commercially available since the early 1990s, but the pace of adoption among U.S. farmers has been modest. This study examines the relationship between the adoption of diagnostic and application techniques of precision farming and sources of information available to farmers about precision farming. The model used in the analysis accounts for sources of self-selection in the adoption process that could bias the results. Results indicate interpersonal information sources have increased adoption relative to information from the mass media, and the private sector has been the driving force behind the diffusion of precision farming. Information from crop consultants and input suppliers has had the greatest impact on the adoption of precision farming technologies. These sources likely provide the greatest technical expertise about precision farming, and thus are better equipped to ease the significant human capital requirement of precision farming technologies.

Fig. 3. Showing an automated precision maching carrying out a variable rate command.

1.3.0GLOBAL ADOPTION OF PRECISION AGRICULTURE TECHNOLOGIES
The adoption of precision agriculture technologies has been uneven, both geographically andtemporally. The economic theory of induced innovation predicts that new technologies will be developed and adopted where they make more efficient use of the scarcest productiveresources. Indeed, adoption of precision agriculture technologies has been fastest where labouris costly but land and capital are relatively less costly. Where precision agriculture is beingadopted, the uneven adoption rate is tied to normal cycles for replacing the expensivemachinery in which many precision agriculture technologies are embodied. Equipmentreplacement decisions are affected by many factors exogenous to the farm, such as bankinterest rates and commodity prices. Adoption is likely to continue in labor-scarce, land-abundant countries, with rates of adoption accelerating when commodity prices are high andinterest rates low.
Although spatial precision agriculture (PA) encompasses four key information technologies, farmers tend to use it in one of two major ways. The four PA technologies include location determination (via the Global Positioning System, GPS), computerized geographicinformation systems (GIS), computer-guided controllers for variable rate application (VRA)of crop inputs, and sensing technologies for automated data collection and mapping. TheGPS and GIS technologies underpin both of the major PA practices that farmers have begunto adopt. One of these is nutrient management; it involves spatially referenced soil sampling, often linked to VRA fertilizer spreading. The other is yield monitoring, usually tied to yieldmapping. In North America adoption is emerging for variants of these, such as VRA seedingand pesticide spraying, as well as remote sensing of plant vigor (Daberkow and McBride,2000).
Some farmers adopt technology while others do not, due to different reasons. Either way, the pattern of PAtechnology adoption has been uneven. Despite the rapid growth of global commerce and thewidespread availability of equipment for VRA and yield monitoring, adoption rates appear todiffer sharply from one country to another, at least based on the informal data available (Norton and Swinton, 2001). Yield monitors are being adopted rapidly in Argentina, but lessso in Brazil or in France. Site-specific fertilizer use is rare in Argentina, despite the growth ofyield monitor use (Lowenberg-DeBoer, 1999). In Malaysia, site-specific fertilization is beingapplied to rubber plantations, but not to rice fields. Even within a country such as the UnitedStates, PA adoption rates vary by a factor of ten – from 11.3% of farms in the Midwestern???Heartland??? to only 1.1% in the Southeastern Seaboard in 1998 (Daberkow and McBride,2000). In general, we observe that in favored areas adoption of yield monitoring or VRAfertilization has surpassed 5 percent only in the United States and Canada. It would appearthat adoption rates in the 1-5 percent range (again, only for favored subregions) may pertaining Australia, Brazil, Denmark, United Kingdom, and Germany. With the exception of a fewyield monitors in South Africa and some VRA fertilization in isolated plantation agricultureenclaves, adoption of PA technologies is virtually unknown in Africa.Rate of adoption is not smoothJudging from trends observed in the United States, PA technology adoption is uneven notonly geographically, but also temporally. The uneven adoption trendcontrasts sharply with the rapid, smooth adoption of hybrid maize following its commercial introduction about 80 years ago (Griliches, 1957; Lowenberg-DeBoer, 1998). Given thepotential benefits of precision agriculture for farm profitability and environmental protection, these uneven adoption patterns may seempuzzling.Agricultural technologies can be viewed as means by which farmers seek to achieve theirproduction objectives. Farmers have many objectives, including risk management, quality oflife, and environmental stewardship. But for the majority of farmers, who rely on agriculturalincome, expected profitability is the sine qua non, they must earn enough to stay in business.In attempting to produce profitably, farmers are constrained by limited access to essential productive resources such as land, labor, equipment, buildings, and management knowledge.
Two characteristics are likely to drive the adoption of PA technologies. First, considering thatthey improve the efficiency of input use in mechanized agriculture, they are likely to beadopted first in those places where input use is already relatively efficient. Second, becausethese technologies use costly capital to automate human information processing, they will bemost attractive where capital is abundant relative to management labor.

1.4 0 A BRIEF HISTORY OF WORLD PRECISION FARMING
Ever since man appeared on the earth, he has been harnessing the natural resources to meet his basic requirements. Reference to soil, water and air as basic resources, their management and means to keep them pure are mentioned in the Vedas, Upanishads and in ancient Hindu literature. The phenomenal increase in population of both man and animal in the last century and fast growing industrialization and urbanization in last few decades have overstrained the natural resource base, which are getting degraded much faster than ever before. Thus, the attention of whole world is focused on how to increase production to feed the burgeoning population and the question uppermost in every ones mind is ???Can we produce enough food in a sustainable manner without damage to the natural resource base???
For over the last 15 years, precision agriculture has been practice in some parts of the world and despite its promising future, it has not yet managed to be adapted globally by farmers.
To the Europeans, Precision Farming is old traditional farming in the modern way. Initially, precision farming took the form of a move away from blanket applications of inputs, increasing in sophistication as developments in technology advanced to enable variable application rates only applying fertilizer and chemicals where they are required and at the optimum rate. Generally, the adoption of precision farming has been modest in Europe as it is advancing to livestock precision application e.g. robotic milking of cattle and the possibility to determine the satisfaction rate of the beast using his ???moo??™ sound. And also, the potential for using precision agriculture to address environmental, food safety, animal welfare and sustainability problems seems to be attracting political attention in Europe. Amongst all this good that have befalling upon the European system of agriculture, there are still some lapses in the southern part of Europe where only a few countries e.g. France, Spain, and Portugal have been very successful with breaking loose from their traditional pattern of agriculture.
The American??™s attitudes of doing things in a unique format have always paved a way for them around the blue globe. This is evident on their adoption of precision farming as they grow rapidly with the aim of input minimization and output maximization. Series of achievements have been made by the Americans within this few years of the emergence op precision agriculture the most striking of them all is the commissioning of a GPS system developed for and managed by the U.S. defense department. Precision farming in America has been very successful as it has been adopted by several countries especially Argentina, U.S.A., Columbia, Brazil, Chile, etcetera.
Australian growers are finding practical and profitable uses for precision agriculture, but the uses differ somewhat from those common in the US. Yield monitoring is relatively common, but as in the US many yield monitors are not linked to global positioning systems (GPS). High soil testing costs have discouraged US style variable rate fertilizer and growers are searching for alternative ways to develop variable rate application (VRA) fertilizer recommendation maps. Because of severe soil compaction problems, GPS guidance for controlled traffic is considered by some to be the best starting point for precision agriculture.
Asia, a world of science and technology, a place where at the mention of the word ???innovation??™, one is welcomed as an ambassador of the jet age. In countries like Japan, small areas are utilized in farming by using greenhouses to plant crops and vegetables. Japanese farmers are equipped with skills in such a way that production can be done simultaneously, thus, making large production at small areas by as many farmers as possible???. By this medium, the Japanese government has been able to lunch a campaign against hunger and corruption in the country. China, being the back bone of Asia technology growth as found a way to defy the might of the GPS scarcity their by reducing the problems of traffic in precision agriculture by the lunching of space satellites to manage field monitoring activities. Some great nations like Taiwan, Japan, China, Korea, and etcetera have found a way to embrace and manage precision farming for the betterment of their world.
Africa being the most backward technologic-wise among all continents as just a little to show for precision farming. Some countries like South Africa and Zambia tops the chart of Nigeria precision farmers while other countries like Nigeria, Cameroon, Ghana, Kenya etcetera only applied some precision operations into mechanized farming.
Precision farming as developed over the past decade, having is origin in Europe. As often the case with new technologies, this practice was taken up in the US and developed at great past. Precision farming is about to change the face of agriculture, as we know it today. Precision farming has been developed mainly in Europe (Moore 1998a). It has, however, been adapted by North American farmers in far greater numbers than in any other part of the world. Various sources show that probably around 90% of all precision farming system operates in US and Canada (Starck, 1998).

1.5.0 PRECISION FARMING IN NIGERIA
Precision farming provides a new solution using a systems approach for todays agricultural issues such as the need to balance productivity with environmental concerns. It is based on advanced information technology. It includes describing and modeling variation in soils and plant species, and integrating agricultural practices to meet site-specific requirements. It aims at increased economic returns, as well as at reducing the energy input and the environmental impact of agriculture. This is very possible in Nigeria if only Nigerians will allow it be, putting together a combined effort to achieving the highest point of application of farming technologies.

1.5.1 A New Concept;
This article is concentrated on the possibilities of the introduction of precision agriculture in Nigeria. Of a truth, there is no such thing as precision farming presently in Nigeria today because all there is are some elements of precision agriculture like the use of sensors and some field monitoring devices to manage crop yield, productivities, variation in soil nutrients and climatic changes as they affect food availabilities. For example in kwara state, yield monitors are been use to monitor the production of selenium production. This practice is been supported by kwara state government as a preferred way of site specific management.
Actually, precision agriculture as a new concept In Nigeria if adapted will bring about a sudden transition from traditional farming (as practiced in most parts of Nigeria) to a better and more advanced level of farm variability management. This whole scenario will involve an experience of the term ???evolution??™ in its entirety. Apart from the self motivation required of Nigerians and monetary support on the part of the Nigeria government, there are other challenges faced by the nation that will militate against the introduction and proper functioning of precision farming in Nigeria. But before we delve into this sub problem proper, lets first take a look into the geography of Nigeria to see if the land his been favored by nature for this effect.

1.5.2 Precision Farming VS Traditional Farming;
just like in a football match between Manchester united FC and Chelsea FC, there is absolutely no basis for comparism between both club teams because Chelsea f c is of no match for man u. precision agriculture have in time encompass traditional farming in all ratification. The advent of machine aided implement with precise application of variable technology to the farmland form the basis and justification of precision agriculture. Just as in the game of football, all the department of precision agriculture works more than those of traditional farming also called (which can either be hand-tool or draught- animal farming). also, the variation in quality, quantity and production factor differs a great deal. Never the less, tradition agriculture is the ancestor of precision agriculture and this is the more reason why Nigerians should embrace precision farming and move forward on the field.
1.6.0 GEOGRAPHY OF NIGERIA
Nigeria, one-third larger than Texas and the most populous country in Africa, is situated on the Gulf of Guinea in West Africa. Its neighbors are Benin, Niger, Cameroon, and Chad. The lower course of the Niger River flows south through the western part of the country into the Gulf of Guinea. Swamps and mangrove forests border the southern coast; inland are hardwood forests.
The first inhabitants of what is now Nigeria were thought to have been the Nok people (500 BC ??“c. AD 200). The Kanuri, Hausa, and Fulani peoples subsequently migrated there. Islam was introduced in the 13th century, and the empire of Kanem controlled the area from the end of the 11th century to the 14th. The Fulani Empire ruled the region from the beginning of the 19th century until the British annexed Lagos in 1851 and seized control of the rest of the region by 1886. It formally became the Colony and Protectorate of Nigeria in 1914.
Nigeria has two broad belts of vegetation types, namely, the forest and savannah types. There is, however, also the mountain vegetation of the isolated high plateau regions in the central and far eastern parts of the country.
Fig.4. a map of Nigeria showing the major towns and cities.
The subhumid zone of Nigeria covers 455 000 km2 or approximately half of Nigeria and a third of the zone in West Africa.
Typically low in carbon and nitrogen, the soils have a tendency to form hard crusts. They have a poor capacity for retaining nutrients, poor water penetration and shallow water tables, all of which adversely affect cropping potential.
Rainfall in the zone ranges from 1000 to 1500 mm, with growing season from 180 to 300 days per year. The zone offers a wide variety of cropping options, but the growing season is invariably punctuated by dry spells. There is high runoff. During the growing season the humidity is conducive to pathogen survival and transmission. In the dry season the vegetation is subject to burning
The zone has five vegetation subzones, but the Guinea and derived savanna subzones account for some 90% of the zone. There is good vegetation cover, although it is dominated by varieties suited to impoverished soil conditions. The feed quality of the grasses rises after the onset of the rains, but declines rapidly after they stop and is low for most of the year. The pattern of vegetation and land use form a mosaic of medium to high levels of cultivation, grassland and woodland. Twenty percent of the zone is cultivated, and cultivation is expanding at 4.8% per annum. It is estimated that by the turn of the century 33% will be cultivated. This estimate is well below the former one of 70%.
Crop yields cannot be sustained on cleared land for more than 3 years without fertilizer or manure. There are opportunities for introducing forage legumes, but such interventions must be in accord with intricate and well established mixed cropping systems. The bigger the contribution of forage legumes to soil fertility and hence to food crop yields, the better the chances of their adoption.
1.6.1 Vegetation zones in Nigeria;
Vegetation, simply defined, is the plant cover of the earth consisting of assemblages of plants. Broadly speaking, the national vegetation over a geographical area is essentially a response to the climate in that area. Nigerias vegetation belts reflect this very close link between vegetation and climate. Hence, the similarity in the west-to-east zonation of both climate and vegetation. With the south to north progressive decline in total rainfall and length of wet season, vegetation belts are demarcated on west-to-east zonation pattern characterized by transitional zones from one belt to another.
The forest vegetation zone of Nigeria consists of;
1. Saline water swamp
2. Freshwater swamp
3. Tropical evergreen rainforest.
While the savannah vegetation zone of Nigeria consist of;
1. Guinea Savannah
2. Sudan Savannah; and
3. Sahel Savannah.
One major characteristic of savannah vegetation is that trees vary in size and density from the Guinea, through the Sudan, to the Sahel Savannah.
If all this are as correct as they seem, then nature her self must have specially designed Nigeria as a country in a unique manner, giving her a format that will favor all manner of crop as their production possibility strength varies across the various vegetation zones. Also, the soil type distribution in Nigeria is in a unique format varying from sand to gravel in different parts of the country and this is one reason why the nation is very rich in minerals and natural resources. Putting all this together, it is evident that the Nigeria geography is by no means a factor or an excuse militating against the adoption and growth of precision farming with as its innovative ideas.
1.6.2 Geology
More than half of the Nigerian subhumid zone is covered by Pre- to Upper Cambrian basement complex. It includes the oldest rocks known in Nigeria, principally composed of metamorphic and igneous material. Over most of the area underlain by basement complex there is a discontinuous mantle of weathered gneiss and granite, but this is generally thin, with a high clay content, and does not serve as an efficient aquifer. The water tables are shallow and adversely affect crops and cropping potentials at the height of the wet season. The soil tends to form a hard crust after the first rains, effectively preventing penetration of water and seedling emergence. It therefore needs tillage for cropping. Areas with excessively coarse materials, a poor capacity for retaining nutrients due to low cation exchange capacity, and topography exceeding 2-3% slope are normally avoided by farmers. Under the traditional production system long fallow periods are necessary for maintaining soil fertility.
1.6.3 Relief
For an area covering half a million square kilometres, the variation in relief within the subhumid zone is limited. Four major relief types can be identified:
The Niger-Benue trough is a Y-shaped lowland area which divides the subhumid zone into three parts. It has been deeply dissected by erosion into tabular hills separated by river valleys. The Niger section is especially rugged.
The upland areas north of the Niger-Benue trough, and west of the Niger river, are generally undulating and strongly marked by inselbergs. The north-central plateau is made up of two different platforms – the high plains of Hausaland, which at an average height of 600 m a.s.l form the first step, and the Jos Plateau at an elevation of between 1000 and 1800 m forming the second step. The latter falls outside the subhumid zone.
The area south of the Benue and east of the Niger, extending eastwards as far as 9?30E, consists of the lowland Cross River plains, east of Enugu, which show outcrops of limestone and shales whereas the relief in general is gentle; and the scarplands west of Enugu, which are made up of the Udi and Awka-Orlu plateaux.
1.6.4 Sunshine and radiation
The maximum seasonal variation in day length in Nigeria is 1 hour and 45 minutes. This variation is sufficient to cause differences in the performance of crops sensitive to photoperiodism. The mean annual number of hours of sunshine increases progressively to the northeast. The daily mean duration of sunshine in July, at the height of the rainy season, is greater in the north than in the south, where the cloud cover is more constant. The same pattern is observed in January, when there is a general lack of cloud cover in the north, but due to humid air from the Gulf of Guinea cloudiness may be expected in the south. This results in a marked zonal pattern when the whole of Nigeria is considered. The northern part of the subhumid zone stands out as having the highest national values of net radiation. Further to the north, outside the zone, surface albedo is higher, reducing net received radiation.

1.6.5 Rainfall
Most of the Nigerian subhumid zone lies between the 1000 mm and 1500 mm isohyets, offering a wide choice of crop options. Rainfall is governed by the annual passage of the Inter-Tropical Convergence Zone (ITCZ), the meeting point of a dry northeastern low-pressure air mass and a moist southwestern high-pressure air mass. The northeastern movement of the ITCZ and the rain-bearing winds that accompany it mark the onset of the rainy season. Its southwestward movement and the accompanying harmattan winds mark the beginning of the dry season. Annual rainfall and its reliability decrease from the south northwards.
The northern part of the zone has unimodal rainfall distribution in which rains increase in frequency and amount, beginning in May and peaking in August. In the southern part the rainfall pattern is bimodal, the first peak occurring in June-July, and the second in September, with August relatively dry. Variations in annual rainfall make it difficult to draw a strict geographical boundary between these two distribution patterns. Much of the subhumid zone is transitional between unimodal and bimodal rainfall distribution.
The rains are expected to reach the southern boundary of the subhumid zone at the beginning of March, and the northern boundary 2 months later (Walter, 1968). At the northern boundary the rainy season normally ends in early October, and at the southern boundary 6 weeks later. The expected duration of the wet season in the subhumid zone thus ranges from 5 months in the north to more than 8 months in the south. Nevertheless the season (April to October) is invariably punctuated by dry spells, the length of which varies from a few days to a few weeks.
Evapotranspiration exceeds rainfall north of latitude 7?°30N (Kowal and Knabe, 1972), although almost everywhere in the zone there appears to be a period of water surplus in the year when rainfall exceeds evapotranspiration. Rainfall is usually torrential, 25 to 50 mm or more often falling within 1 hour. Measurement of infiltration or rainfall acceptance on a ferruginous soil type using catchment gauges gave an average ultimate infiltration of 24 mm/hour. Rainfall exceeding this rate can cause serious erosion and runoff. High humidity and concentrated rainfall during the growing season are conducive to pathogen survival and transmission. The dry season, on the other hand, is severe and the vegetation becomes parched and easily combustible.
1.6.6 Major soil types
Ferruginous tropical soils cover approximately half the Nigerian subhumid zone. These soils are generally characterized by a sandy surface horizon overlying a weakly structured clay accumulation. Their base-exchange capacity is low, but their base saturation and pH values are relatively high. They have high natural fertility, and FAO (1966) rates them as having good potential. However, under traditional management practices ferruginous tropical soils are of low productivity, are sensitive to erosion and have low water-holding capacity.
The alluvial soils found along the Niger and Benue rivers show light accumulations of organic matter but are often, under traditional management practices, too wet during the rainy season for crops other than rice. Under improved management practices, including irrigation and drainage, these soils have been classified by FAO (1966) as having strong to good potential, depending on their local texture and salt content.
The ferralsols that occupy much of the other half of Nigerias subhumid zone are deep, strongly weathered soils of friable consistency. They have a low base-exchange capacity, low pH values and generally low nutrient contents. However, their resistance to erosion and good physical properties make these soils suitable for a wide range of crops. The ferralsols within the subhumid zone are categorized by FAO as soils of low present productivity, but as having medium potential if their management can be improved.
The lithosols found in the north-central part of the zone are of local significance only, and have been classified by FAO as being of variable productivity and potential. Under traditional management they are dry for 6 to 8 months of the year. In addition they are shallow, moderately leached with little organic matter, and have a low base-exchange capacity.
The vertisols found in a small area west of Yola are difficult to work under traditional management practices. They crack deeply when dry, and have a heavy dark texture when moist. They are therefore of only medium productivity, in spite of being generally high in nutrients. Under improved management practices, FAO classifies these soils as having good potential.
The soil properties in ILCAs case study areas are shown in Table 1.
Table 1. General soil properties in two ILCA case study areas.
Location | pH | Organic
C (% | Total
N (%) | Available
P (ppm) | Ca
(Meg/100 g) | Mg
(Meg/100 g) | Mn
(Meg/100 g) | K
(Meg/100 g) | Total acidity |
Kurmin Biri | 5.2 | 0.58 | 0.071 | 3.9 | 1.12 | 0.37 | 0.02 | 0.13 | 0.78 |
Abet | 5.3 | 0.36 | 0.086 | 1.8 | 1.04 | 0.49 | 0.11 | 0.13 | 0.46 |
1.6.7 Vegetation and land use;
The subhumid zone includes five vegetation subzones, excluding those found at high altitude. The Guinea and derived savanna subzones occupy some 90% of the area. The areas of Nigeria where mans influence on the vegetation is greatest lie to the north and south of the subhumid zone, exemplified by conditions in the Sahel and by the diminishing rain forest. Blair-Rains (1968) stated that the existing vegetation in Nigeria in general may bear little resemblance to the original zonal categories, because of the combined effects of human activity: burning, cultivation, tree felling and cattle grazing.
Extensive areas of medium to high levels of land-use intensity are found on the northern border of the subhumid zone extending northwards, with the highest cultivation density being associated with major towns. The same pattern is found on the southern border, around Enugu, and southwards, where the proportion of land cultivated reaches its highest, at 25%. The land in between these two areas falls within the subhumid zone, where cultivation declines to some 17%. Here the pattern of vegetation and land use can best be described as a mosaic of varying levels of cultivation, grassland and woodland. An interconnecting patchwork of more intense cultivation links the northern and southern cultivated regions of Nigeria, through a broad belt north of Lokoja including Bida, Minna, Abuja, Lafia, Shendam, Kafanchan, the Jos Plateau, Kaduna and Saminaka. In this belt, cultivation reaches a peak of 35%. To the west and east of it, cultivated areas are generally more scattered (10%) with woodland tending to predominate.
1.6.8 Distribution of cultivation
Bourn and Milligan (1983) estimated 20% of the Nigerian subhumid zone to be under cultivation. The overall distribution of this farmland, and hence the intensity of land use, are represented by the three-dimensional surface shown in Figure 1, in which the proportion of land under cultivation is indicated by apparent height. As already suggested by the side-looking airborne radar (SLAR) vegetation and land-use map, cultivation was found to be unevenly distributed within the subhumid zone, being concentrated in a series of semi-isolated peaks of high-intensity land use, surrounded by areas of relatively low cultivation. However, an important feature indicated in Figure 1 but not evident on the SLAR map is that cultivation is taking place throughout the surveyed area, albeit at very low levels in the more western areas and to the southeast.
Putt et al (1980) have demonstrated a rapid rate of agricultural expansion, associated with human population increase, both within and outside the subhumid zone. In the Lafia region, for example, comparative airphoto-interpretation indicated that cultivation was expanding at an annual rate of 4.8%. Assuming continued expansion at that rate (plus or minus 1%) and an estimated 20% of the zone to be cultivated at present, Figure 2 projects the increasing proportion likely to be under cultivation to the turn of the century. Even the higher estimate of 33.1% under cultivation is very much below the previous estimate of 70% for the zone as a whole (ILCA, 1979). Since approximately one third of the West African sub humid zone is in Nigeria, the figure of 70% would appear to be an overestimate.

Fig.5. showing the distribution of cultivation
1.6.9 Forage resources;
The herbaceous cover of the subhumid zone consists mainly of annual grasses, with a very low percentage of native legumes. Seasonal changes in herbage quality are primarily due more to changes in plant development than to climatic conditions per se. The C4 photosynthetic pathways in grasses promote a rapid accumulation of structural components, resulting in dilution of nutrients such as N and P in the tissue. Legumes on the other hand, exhibit a less efficient C3 photosynthetic pathway and are independent of soil N. which is secured through biological fixation in the root nodules. Legumes are therefore usually higher in protein and minerals and have higher dry matter (DM) digestibility and voluntary intake by animals than do grasses at similar stages of growth. Growing forage legumes should thus provide a means of overcoming the protein deficiency of the grasses which dominate natural feed supplies.
1.6.10Forage productivity;
1.6.10.1 Measurement
Land-use patterns affect the productivity of natural forage. Because of its favourable rainfall the subhumid zone is also likely to be increasingly utilized for cropping wherever edaphic and other conditions are favourable. Forage productivity measurements were carried out in two environments where pastoralists are settling:
1. An intensive arable farming area (Abet).
2. An area reserved by the state for grazing (Kurmin Biri Kachia).
An inventory, and the frequency, of existing flora in the herbaceous cover were compiled by using line transects. A number of transects were read in three distinct ecological niches in each study area.
Potential yield of the herbaceous strata of the three ecological subdivisions was estimated from five samples of 1 m2 each, clipped to ground level at the beginning and end of the rains, within a 5 x 5 m enclosed area protected from livestock throughout the growing season. Monthly forage production and botanical composition were also estimated from 1 m2 samples, clipped to the ground within similar enclosures as above, but moved randomly after each monthly clipping. Weight difference or DM disappearance between clipped samples from within and outside the enclosures was assumed to have been grazed by livestock during that month. Cut samples, hand-separated into grass and non-grass (forb), were taken, dried and analysed for crude protein (CP) and DM digestibility. Data collected from the three ecological subdivisions were pooled to construct a generalized pattern of forage production in the subhumid zone (Figures 3 and 4).
One season of uninterrupted growth of the herbaceous stratum in a burnt area in the subhumid zone produced a DM yield of 2250 kg on shallow, ferruginous soils. Fadama (lowland) soils, with deep hydromorphology, tend to support higher DM productivity – up to 5 tonnes in one growing season (Table 2). On this soil type forage growth is prolonged by residual moisture long after the rains have ceased (Figure 5).

Fig.6
Table 2. One seasons DM production (kg/ha)a/ of the herbaceous layer in different eco-subsystems in two study areas of the subhumid zone of Nigeria.
| Fadama | Woodland | Scrubland | Riverine |
Kurmin Biri | 3754 | 1758 | 2251 | 2156 |
Abet | 4922 | – | 2185 | 1940 |
a/ Uninterrupted growth.
Herbage growth and production varies seasonally, and the maximum herbaceous biomass on offer is attained between August-September (Figures 3 and 4). Seasonality of production also affects non-graminoid components, and their proportion in the total biomass is higher at the beginning of the rainy season (Table 3). Non-graminaceous types are insignificant in the herbaceous layer, especially in burnt areas.
Productivity of the herbaceous cover also varies between years. Herbage produced in the fadama at Abet was about 1 tonne higher in 1981 when the area received 167 mm more rain than the previous year. Both seasonal and species differences contribute to changes in forage quality. During their early development grasses increase in protein content. Where conditions are favourable, the release of soil nitrogen early in the growing season may increase their CP to 9%. But once the rains are over CP content declines rapidly, and since the main bulk of forage on offer is grass, the overall nutritive value of the herbaceous cover in terms of protein is low for most of the year.
Table 3. Botanical composition of the herbaceous layer of two ILCA case study areas in the subhumid zone of Nigeria (kg/ha).
Study area/Months | Grass | Forb | Total | % Forb |
Kurmin Biri |
January | 612 | – | 612 | – |
February | 504 | – | 504 | – |
March | 144 | 76 | 220 | 34 |
April | 288 | 172 | 460 | 37 |
May | 714 | 206 | 920 | 22 |
June | 1573 | 301 | 1874 | 16 |
July | 1799 | 368 | 2162 | 17 |
August | 2298 | 431 | 2729 | 16 |
September | 2380 | 437 | 2817 | 18 |
October | 1980 | 386 | 2366 | 16 |
November | 1200 | 285 | 1485 | 19 |
December | 826 | 165 | 991 | 20 |
Abet |
January | 1382 | – | 1382 | – |
February | 322 | – | 322 | – |
March | 290 | – | 290 | – |
April | 518 | 93 | 611 | 15 |
May | 910 | 203 | 1113 | 18 |
June | 1502 | 328 | 1830 | 18 |
July | 2193 | 166 | 2359 | 7 |
August | 2811 | 189 | 3000 | 6 |
September | 3094 | 226 | 3320 | 7 |
October | 2729 | 218 | 2947 | 7 |
November | 2688 | 163 | 2851 | 6 |
December | 2212 | 94 | 2306 | 4 |
The digestibility of grass is low throughout the year (Figures 3 and 4). It exceeds 40% for only 4 months during the growing season, when the tissues are tender. Digestibility changes closely follow the level of protein in the tissue (Figure 6). This correlation highlights the importance of increasing protein levels in the forage.

Fig. 7
Livestock, through selective grazing, tend to consume a better quality diet than average protein and digestibility levels would suggest. Analyses of grab samples collected by following animals showed higher protein content and digestibility throughout the year (Figure 7). The overall quality of forage from a burnt area was also higher. Burning as early as October-November increased the quality of regrown forage, but the bulk left at the end of the growing season was very low in quality and therefore less utilized by livestock, which prefer the new flush of shoots induced by burning (Figures 3 and 4).

fig. 8.
Indications are that forage utilization in more intensively farmed areas is higher than in other areas, possibly because of the tendency of pastoralists to settle near arable farmers.
1.6.11Forage composition and availability
The sub humid zone has good ground vegetative cover. Empty spaces in any area account for 8 to 17%, depending on the type of soil, available moisture and the level of land use. Grasses make up about 62 to 82% of the total herbaceous forage. Leguminous species are very low. Other short-growing dicots, associated with grass, make up about 10 to 20% of herbaceous cover (Table 4).

Table 4. Composition of the herbaceous cover of three eco-subsystems of the subhumid zone (%).
| Eco-subsystem |
Plant cover | Fadama | Scrubland | Riverine |
Total plant cover | 92.1 | 83.7 | 83.2 |
Grass | 82.0 | 64.2 | 62.3 |
Legumes | 0.7 | 4.4 | 1.4 |
Others | 9.4 | 15.1 | 19.5 |
On the basis of percentage frequency, Rattray (1960) used a given grass genus that emerged as the dominating type to designate a particular climatic zone. Accordingly, the subhumid zone of West Africa could be divided into three belts that cross the south-north axis: the Pennisetum, Hyparrhenia and Andropogon belts. These dominant species have given way to others over the years, doubtless as a result of human influence. The graminoid types in both the ILCA study areas are dominated by Loudetia simplex, which is a tufted perennial, suggesting impoverished soil conditions (Table 5).
Table 5. Frequency distribution of the major grasses in the herbaceous cover of the Kachia Grazing Reserve.
Grasses | Occurrence (%) |
Andropogon spp. | 6.2 |
Brachiaria spp. | 8.3 |
Digitaria spp. | 0.8 |
Hyparrhenia spp. | 11.4 |
Loudetia spp. | 40.7 |
Panicum spp. | 0.8 |
Paspalum spp. | 1.4 |
Setaria spp. | 0.6 |

1.6.12Forage constraints and interventions
1.6.12.1Cropland
Land cleared and prepared for cropping has an unprotected surface and therefore deteriorates rapidly under the impact of the torrential rains typical of the subhumid zone. Clearing increases surface runoff and leaching of nutrients. Moreover, the temperature of an unprotected soil surface tends to be higher, which encourages more rapid decomposition of organic matter than in a soil with a natural vegetative cover. Soil undergoing degradation at such a rate cannot support continuous cropping unless its lost properties are restored in some way. When such a soil is cropped repeatedly, crop yields decline and the capacity of the land to support human life diminishes with time (Table 6). Experienced farmers are able to predict the time limit for profitable cropping once an area is cleared, which generally ranges from 1 to 3 years unless manure or fertilizer is applied.
Table 6. Productivity of sorghum (kg/ha) when cropped for 3 years continuously with or without manure additions (Kurmin Biri, 1981-1983)a/.
? | Year |
| 1981 | 1982 | 1983b/ |
Without animal manure | | | |
| Grain yield | 858 | 690 | 267 |
| Crop residue | 4330 | 3740 | 2133 |
With animal manure | | | |
| Grain yield | – | 1352 | 933 |
| Crop residue | – | 5710 | 4000 |
Each replicate in the trial was divided into two, and 20 to 30 animals were confined for 5 days on one half, prior to land preparation in 1982 and 1983.
b/ In 1983 there was a very short wet season compared with previous years.
Soil fertility is traditionally restored by fallowing. The length of time the soil is rested after cropping is generally a function of population pressure. Where population is low, rest periods between cultivated phases may be prolonged, resulting in a low cropping index. In this system a farmer has to clear a new area for cultivation each time he abandons the old one. Soil restoration is left to take a natural but prolonged course with no inputs from the farmer. Areas with a low cropping index can provide reasonably well regenerated land whenever this is required by farmers,
Higher population levels make prolonged fallow periods less feasible. Farmers are obliged to return to a previously cropped area much sooner. Incomplete recovery then has to be compensated by additional inputs to make the soil productive. The return of ash, household sweepings, night soil and, of course, fertilizers to the land are some of the measures used.
For the farmers in parts of Nigerias sub humid zone, access to manure plays a very significant role in the maintenance of soil fertility with or without short rest periods. Manure allows intensive cropping and hence higher human support capacity per unit area of land. Crop and livestock production are commonly carried out by ethnically separate communities, although mixed farming is increasing in Nigeria. Fulani pastoralists prefer to settle in the vicinity of cereal farmers, who thus have access to manure even if they do not own livestock themselves. Animals can also be used for traction and transport, besides being a source of much needed protein.
For all the contributions of livestock, the crop sector at the moment tends to offer only crop residues and unimproved fallows in return. Although valuable to livestock early in the dry season (Paper 14), crop residues alone are inadequate to meet the nutritional demands of animals.
Growing cereal crops and forage legumes in a mixture is a recent concept in African agriculture. Both components in the mixture require a different production emphasis (grain from cereals and hence emphasis on the reproductive phase, but herbage from legumes, and hence emphasis on the vegetative stage). The agronomic requirements of a cereal/forage crop mixture differ from those of other conventional crop mixtures.
Research carried out by ILCA in the past 3 years indicates that forage legumes can be incorporated into existing cropping systems by simple adjustments of sowing time, plant densities or planting sequences. These adjustments improve the nutritive value of crop residues and hence the economic returns per unit area of land.
Mixed cropping is the basic farming practice in the sub humid zone of Nigeria. Sorghum is the principal crop and predominates in the different crop mixtures. Most commonly, it is intercropped with soybean and/or maize, but various other crops, such as groundnut, cowpea, millet, and okra, also feature.
Farmers reasons for growing a mixture of crops are to minimize risk, spread labour inputs, and reduce disease problems (Evans, 1960; Norman, 1974). These advantages outweigh the benefits of sole cropping, and mixed cropping will doubtlessly remain the standard practice in the sub humid zone for the foreseeable future. Yield advantages in mixed as compared to sole cropping are also common when the component crops complement each other. This happens when their growth patterns differ in time, so that each crop makes its major demands on resources at different times (Wiley, 1979). It will be possible to incorporate forage legumes into crop mixtures only if appropriate adjustments can be made to cropping patterns. These adjustments should not be too far removed from the existing practices if they are to be adopted easily by the farmers.
1.6.12.2Rangeland
Natural forage provides the cheapest source of nutrients for ruminants, but the land on which it grows does not often have a high capacity for biomass production. The deflected or disclimax vegetations typical of such land are also likely to increase with the spread of human activity into areas which are as yet underutilized. These areas will not revert back to climax floral associations whilst under continued pressure from man and stock.
Livestock grazing natural rangeland derive most of their feed from grasses, with browse becoming increasingly important (but never dominant) as the dry season progresses.
High costs and the communal ownership of rangeland preclude large-scale pasture development in Nigerias subhumid zone. Unrestricted access and widespread burning have so far frustrated conventional range management strategies. Small units of sown forage might nevertheless be respected on private property just as cereal crops are. The Fulani in the ILCA case study areas have traditionally sown fonio (Digitaria exilis) on areas grazed and trodden by cattle. This technique can be adapted to provide the labour required for legume establishment. Small units are probably a safer investment than large ones, owing to the risk of fire.

2.0 CHALLENGES
Now, let??™s take a look at the various potential challenges militating against the practice of sustainable precision farming in Nigeria. This set backs are numerously as large as the nation herself but can be grouped into various broad classes as discussed below;
2.1Socio-psychological challenges: being the most critical among the various problems faced by not only precision agriculture but by farming in general, socio-psychology talks about the mind- set of the people about a given concept. In Nigeria today, farming is been perceive as a dirty job since the advent of the so called petroleum which is seen as a white collar job (office job) and as taken over the consciousness of the people. Also, people radar work in an air-conditioning office and receive a low income than aspiring for a better economy in the farming sector. Food scarcity is attaining its climax as hunger, death, and diseases as taking over the peace and unity of the states yet we still wallow in in-depth ignorance. Also, looking at the name ???farming??™ which is the mother name of ???agriculture??™ has been neglected just for the reason of acceptance by the ignorant nation. In most learning institutions in Nigeria, names have been changed from agricultural engineering to biological engineering, bioresources engineering, and etcetera for the senseless reason of rebranding. We talk about enlightening the nation but yet we live in the shadows of our fear for a world full of politics. We bear a name ???national association of agricultural engineer (NIAE)??™ yet we allow the chuckles of fear obtain the better part of us without considering properly what fate in the future have for us. There is no crime on becoming the vibrant minorities were the voice of the people is to be heard and acknowledge for his stronger will and love for his mother land. If proper precautions are not taken, the name ???agricultural engineers??™ will be erased from the pages of history.
The economy of Nigeria historically was based on agriculture, and about 70% of the workforce is still engaged in farming (largely of a subsistence type). The chief crops are cocoa, peanuts, palm oil, corn, rice, sorghum, millet, soybeans, cassava, yams, and rubber. In addition, cattle, sheep, goats, and pigs are raised. But nowadays, Petroleum is the leading mineral produced in Nigeria and provides about 95% of foreign exchange earnings and the majority of government revenues. With oil as a basic source of income for the nation, the government as loosed interest in the farming and everything that concerns the agricultural sector. Now what will be the fate of precision farming in a country where the government pays little or no interest in agriculture
2.2Land tenure system: land ownership and land fragmentization is yet another common factor militating against commercialization in the farming sector. Some may say that commercial farming neutralizes land fragmentization but taking a critical look at the subject matter, they are both linked up one way or the other. Taking for an instance a commercial farmer pledging for a land from a community man having six kid and he is willing to loan the land to the farmer for a period of time but with the permission of his children. If three of the children refuse to loan their portion of the land for some individual reasons, then land fragmentization has directly or indirectly affected agriculture commercialization. Also, land ownership by communities which can only be use by community members as created a restriction for aspiring alien precision farmers their by militating against precision agriculture in such areas of promising yield.
2.3 Technological awareness: Nigeria technology growth is on a creeping motion yet it is regarded as one of the fastest growing technological economy in Africa. Since the official lunching of the GSM device on the 6th of October 2001, there have been series of improvement in the technological sector but Nigerians believe that the best is yet to come.
2.4Infrastructural facilities and basic amenities: when talking about infrastructural facilities and basic amenities as they affect precision farming, it covers the application of precision farming technologies and their variations in time. The first step to be put into consideration to getting started with a full-time precision agriculture after the acquisition of land is the construction of a base centre for data collection, storage, and information command dissemination. This brings us to the challenges militating against the introduction of precision farming in Nigeria. The cost of building a standard base centre in Nigeria is very expensive as it involves the use of un-common and expensive technologies. The various precision technologies are been discussed in detail by Okwudiuche F.O. (2010). Also, the basic amenities required for the proper functioning of precision farming are practically not available in the country. This is a basic set back in the introduction of precision farming in the country. These basic amenities include electricity, road, water, and precision facilities which are the function of the government to provide the country with. Not to talk about the issue of electricity which has become outrageous. The Nigeria road is nothing to write home about and that of the scarcity of a natural resource as free as water is the most disgraceful of it all. Here, it is evident that the introduction of precision farming in Nigeria means rebranding Nigeria for the better, as it affects basically all aspects of living of the people.
Also, precision machines are very expensive to come by especially when they are emerging technologies. There are also some factors to be considered when choosing a precision machine which include the workability of the machine involving weather as a factor in the machine production. Some machines are design to suite into the weather conditions which can be another factor in the design mechanism of a precision machine in other for it to be durable and work precisely. For instance, in the design of a sensors and telemetry for the collection and transmission of data from to the base centre, the weather condition of the region must be put into consideration because the use of sensors and t

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