Ancha Srinivasan

Geospatial Analysis Center
Regional Science Institute
Sapporo, Hokkaido, Japan

The growing food demands due to ever-rising human populations forced Asian farmers to adopt resource-intensive and unsustainable practices that increased both economic and environmental costs. Asian farming systems, therefore, present both obstacles and opportunities for adoption of precision agriculture. The paper discusses the current status of Asian agriculture and various constraints to adoption of precision farming. The situations in which precision farming may be the most rewarding and offer the greatest environmental benefits are highlighted. The technical, management and social issues, and implications for adoption of precision technologies by small farmers, including the role of the private sector and agricultural associations are discussed. It is concluded that many precision technologies are pertinent for application in even small farms, and that favorable policy support by governments would encourage further adoption.

Tailoring soil and crop management to match varying conditions (soil texture, moisture and nutrient status, pest distribution, etc.) within a field is not entirely new to Asian farmers. The growers traditionally noted yield variability in both space and time, and changed farm practices (e.g., seeding rates) depending on site conditions to optimize soil resources and external inputs. This was possible because most Asian farms were relatively small and farmers were familiar with spatial and temporal variation. However, precision farming in terms of using technologies such as Global Positioning Systems (GPS), Geographic Information Systems (GIS), remote sensing, yield monitors, guidance systems for variable rate application, etc. to manage within-field variation is still in its infancy in Asia.

Ever since the introduction of Green Revolution technologies in 1960s, Asian farmers have tended to treat all fields within a region uniformly resulting in application of inputs to areas not needing them or where the crops cannot make full use of them. It is now well known that such practices are not always in harmony with the environment. In addition, demographic and market changes in industrial Asian countries such as Japan, Taiwan and Korea, are compelling farmers to make decisions that are both economically and environmentally sound. The effective decision making, however, depends on quick and accurate analysis of agronomic data. In this context, precision farming technologies are widely known to assist growers in making informed decisions.

Two basic steps in precision farming include the measurement of variability in a field and the management of such variation by optimizing input application, tillage, cultivar selection, etc. The emphasis on measurement, however, seems to vary in different regions. North American researchers have so far emphasized measuring variation in soil fertility and developing sensors, while the European researchers focussed on producing and characterizing yield maps. While it is important to measure variation as precisely as possible, it is unclear how far collection of precise data per se is effective, for it is not always easy to determine the cause-effect relationships impacting on yield and profitability. This is especially relevant in Asia, where complex cropping systems characterized by high spatial and temporal variation are common. In such cases, it is perhaps more important to simultaneously address the known causes of yield variation while data collection on field variability is in progress. In order to know the relevance of precision farming in Asia, it is essential to examine the current agricultural status.

Agronomic research in Asia was so far mainly targeted to enhance productivity at the farm level in the shortest possible time. As a result, very little attention was paid to monitoring the after-effects of adopted technologies on the quality of the resource base. Precision farming technologies are likely to be of great benefit in addressing this issue. However, as Asian countries and regions are at various stages of technological and economic development, there is considerable diversity in yields and agronomic practices both within and between nations. For example, in northwest India, where intensive farming is common, productivity is similar to that in developed countries. In contrast, the yields in Eastern India are very low. In countries such as Japan, where farm mechanization is more common than in others, grain yields are high but input efficiency is low. The efficiency in farming is thus interpreted variously in different regions but the need for improving farm efficiency and creating systems that are less wasteful and less damaging to the environment than the existing ones, is recognized everywhere.

The enhanced productivity that characterized the Green Revolution era in developing countries of Asia resulted from a combination of factors including the introduction of high yielding varieties, the expansion of irrigated area, and the intensive use of inputs including fertilizers and pesticides. The increase in input use over time has been especially high in Asian countries. For example, in India, chemical fertilizer use rose from a mere 69,000 tons in 1950 to 13.6 million tons in 1995 (Table 1), with many farmers applying high doses of about 400-500 kg nutrients/ha/year. Likewise, the use of pesticides (active ingredient) increased from 2,350 tons in 1950 to 63,270 tons in 1995. Further, nearly 78 out of 124 million ha. of area under food grains were covered by modern varieties in 1995. Despite this intensive input use, growth rates have been dropping recently causing great concern (Table 2). Many farmers realize they need to continue raising the input levels to maintain past yields due to a downward shift in response functions across a wide range of input application rates (Byerlee, 1994). The occurrence of deficiencies of secondary and micro- nutrients has become common and farmers now apply P, K, S, Zn, B, Fe and Mn to alleviate such deficiencies. The intensive cropping systems led to the lowering of groundwater levels to as much as 15 to 20 m with the rate of decline continuing at 0.5-1 m per year. For example, in Punjab and Haryana, the net annual draft exceeded utilizable groundwater resources in as many as 53 and 42% of blocks respectively (Abrol, 1998). The development of insecticide resistance in pests such as cotton bollworm and herbicide resistance in weeds such as Phalaris minor, are forcing growers to use high doses of chemicals without the benefit of effective control. It is, therefore, realized that future gains in input efficiency will have to come from technologies such as precision farming.
 

Table 1. Input use in Indian agriculture from 1950 to 1995.
 

Input	Unit	1950	1960	1970	1980	1995
1. Seeds
a. Breeder seed	Tons	---	---	---	527	3900
b. Certified seed	Million tons	---	---	---	0.25	0.65
2. Chemical fertilizers
a. Nitrogen (N)	Million tons	0.06	0.21	1.49	3.68	9.51
b. Phosphorus (P)	Million tons	0.01	0.05	0.46	1.21	2.93
c. Potassium (K)	Million tons	0.006	0.03	0.23	0.62	1.13
d. NPK use per ha	kg	0.54	1.91	13.13	31.83	75.68
3. Pesticides	Thousand tons	2.35	8.62	24.32	45.00	63.27
4. Irrigation	Million ha.	---	---	38.0	54.1	77.9
5. Electricity	Terawatt h	---	---	---	14.5	70.7

Source: Ministry of Agriculture, Government of India (1996)
 

Table 2. Annual rates of growth in food grain production in India (%)
 

Period	Rice	Wheat	Legumes
1967-1995	2.9	4.7	2.7
1980-1995	3.4	3.6	2.9
1990-1996	1.5	3.6	1.7

Source: Ministry of Agriculture, Government of India (1996)

In industrial Asian countries such as Japan, Taiwan and Korea, a fierce price competition following globalization of markets and demographic changes in farm population are putting extra pressure on agricultural competitiveness. The changes include aging farm populations, a decline in number of full time farmers, and rising costs due to labor shortage. In Japan, up to 58.4% of farmers are 60 years or older. This means that at least one-third of all farmers would retire from farming in a few years. Between 1960 and 1995, the number of farm households dropped from 6 to 3.4 million, and farming population from 34.4 to 15 million. The number of part time farmers also declined by as much as 330,000 households. The numbers decreased by more than 10% in all prefectures from 1990 to 1995, the largest drop ever for any five-year period. In Hokkaido prefecture, for example, the number of farm households declined by about 50,000 over a span of 20 years, and the population engaged in own farming by about 6,000 people per year (Table 3). The positive side of this bleak picture is that farming households with 5 ha or more of farmland in Japan increased from 2,000 in 1960 to 36,000 in 1995.

Table 3. Farming households and population in Hokkaido, Japan
 

Year	Total farm households	Full-time farm households	Farm household population	Population engaged in own farming
1975	134,263	57,491	623,366	303,450
1980	119,644	50,287	532,268	270,520
1985	109,315	47,520	472,180	246,996
1990	95,437	42,582	404,870	215,992
1995	80,987	35,280	333,659	179,607

Source: Hokkaido Department of Agriculture, 1998

Input application in farms of industrial Asian countries has been high for quite a long time, with the result that accumulation of excess nutrients has become a serious problem in some watersheds. Farmers usually apply more than endorsed doses of fertilizers and pesticides because of their relatively low cost and high input subsidies. Soil type is another factor influencing excessive use of fertilizers in some regions. For example, excessive P fertilization is common in Tokachi region of Hokkaido, where Andosols characterized by low bulk density and high P retention, occupy nearly 50% of cultivated lands.

It is important to bear in mind the two major changes occurring all over Asia. First, increased urbanization and migration of people from rural to urban areas is causing a severe labor shortage, which in turn is contributing to an indiscriminate use of chemicals. For example, the direct seeding of rice is gaining appeal in Malaysia, Indonesia and the Mekong Delta, despite major weed problems associated with this system. Herbicide use in these regions, therefore, increased substantially. Secondly, a rapid shift in area out of grains to vegetables and fruits is leading to a shift in resource allocation from land-extensive activities to labor, capital and technology-intensive ones. In view of such changes, Asian growers are likely to use precision farming technologies to remain globally competitive.

Precision farming obviously requires some degree of competence in the use of software and hardware on the part of growers and/or crop consultants. Indeed the success of precision farming largely depends on creation of management systems, which will involve some combination of computerized decision support systems and the wisdom of farmers. Growers will adopt information technologies only if they are reliable and easy to use, offer some competitive advantage and can be introduced into farming without too much difficulty or expense. Larscheid and Blackmore (1996) considered three levels of technology adoption in precision farming, where the first level represents conventional practice and the third level has fully supported variable application rate capability.

A perusal of papers presented at the First Asian Conference for Information Technology in Agriculture held from 24 to 26 January 1998 in Wakayama, Japan, showed that the use of component technologies of precision farming such as GIS and remote sensing is fairly common on a regional basis in Asia. However, there is a wide diversity in stages of technology adoption in various countries. The discussion here is, however, limited mainly to Japan and to aspects other than hardware engineering. Readers interested in hardware engineering may refer to articles by Garcia et al., (1998), Inoue (1998), and Shibata et al., (1998).

Currently there are 36 public agricultural information centers located in 34 out of 43 prefectures in Japan. In addition, the private sector provides farm-related information through joint initiatives. For example, weather news companies and Japan Weather Association provide MaMeDAS, a meteorological data acquisition system for small areas (1 x 1 km). Many farmers use it for farm operation planning especially to decide on time of harvest, pesticide application, etc.

In a typical Japanese farm establishment, it is common to find software such as a business management system, a registration system for attendance, and a system for recording farm practices (Tanaka, 1997). Many farmers use computers and software for basic accounting and irrigation management. There are nearly 150 types of farm software in use in Japan (Table 4). The Japan Rural Information Systems Association developed the Farm Resource Management Support System, which allows farmers to record all field operations. By creating location-specific farm databases, Fujitsu Kyushu System Engineering Ltd. and Fujitsu Hokkaido System Engineering Ltd. developed "AGRIPACK for windows". The Japan Uni-System developed a farm GIS package but its field application has been limited so far. Sorimachi Corp. created many types of farm management software including a GIS "Agricultural Land GIS for Windows". Tottori University is developing another farm GIS software that may be useful in precision farming.

The use of GPS in farming is limited yet but it is fair to expect widespread use of GPS in future. Recently, a GPS-based crop duster (Precision GPS Helicopter), which can spray an area as small as 4 x 4 m, is attracting great attention. Some progressive farmers are now beginning to use GPS for recording observations such as weed growth, unusual plant stress, coloring and growth conditions, which can then be mapped with a GIS program.

Application of remote sensing for regional or landscape studies is common in Asia. Many countries, using an area frame sample, have begun to integrate GIS and remote sensing in their crop inventory statistics programs and as the basis for crop forecast. For instance, Shibasaki et al. (1995) and Changyao (1995) studied land use changes in South East Asia and China respectively using remote sensing, GPS and GIS. In Japan, corporations like Hitachi and Mitsubishi are involved in the launch of satellites in collaboration with the US companies and are attempting to supply data for agricultural use in Asian countries. Remote sensing has also been used in conjunction with GIS for monitoring changes in crop conditions. Mino et al. (1998) used multi-temporal satellite data to distinguish grasslands of different ages, monitor changes in management, and evaluate grassland quality.

The use of remote sensing to estimate soil and plant characteristics is also common. Using Landsat imagery, Okamoto et al. (1990) and Hatanaka et al., (1995) estimated organic matter and available water holding capacity respectively in upland soils of Tokachi district. Likewise, the Central Agricultural Experiment Station estimated land productivity in different regions of Hokkaido after inputting soil and climatic information to a GIS (Shiga, 1997). In the latter study, it was concluded that over a period of 20 years, there was a sharp decline in soil organic matter content in surface soil in Ishikari Plains of Hokkaido, and that yield variation in rice closely corresponded with spatial variation in average temperature. Using Landsat data, Okano et al., (1995, 1997) reported that fields with low soil organic matter tended to produce sugar beet with high sugar content and root weight.

Table 4. Current status of agricultural software in the Japanese market
 

Type of software	Number
Farm operations Management	31
Dairy farm management	30
Farm environmental management	19
Office management/administration	13
Database construction	13
Poultry and Swine management	11
Beef cattle management	9
Labor operations management	8
Sales management	6
Growth monitoring	6
Daily life support software	4
Total	150

Source: Japan Agricultural Software Association (1996)

There are many obstacles to adoption of precision farming in Asia. Some are common to those in other regions but the others are specific to Asian conditions.

Culture and perceptions of the users:

It is widely felt that Asian farmers are resistant to new technologies and do not accept them unless they are fully convinced of benefits. Many growers are also reluctant to share data concerning their fields, as they do not want the information exploited too early by the commodity traders. A preliminary survey in Hokkaido revealed that most farmers do not enjoy record-keeping tasks and believe that precision farming requires additional skills in data management. The planners, on the other hand, believe that running costs in using precision technologies are high. While many growers understand that the intent of precision farming is to manage input needs to achieve maximum economic yield for each area, they are skeptical of how the data is transformed into useful information for farm level decisions. Most farmers in Japan are over 60 years of age and/or part-time, and are reluctant to use computers. Further, they are unaware of agro-environmental problems such as groundwater pollution caused by ineffective fertilization methods. Therefore, the environmental benefits from precision farming need to be popularized.

Small farm size:

The meaning of small farms in Asia is different than in the West. Family farms range from 80 to 120 ha in the US, but they are only from 0.1 to 8 ha in Asia. Land fragmentation and sub-division are common in Asia and slow progress in consolidation is a major obstacle to adoption of precision farming. If typical field size is about 1 ha, it is perhaps necessary to get imagery acquired by a sensor with greater than 1 m resolution. Many studies in the West show that farm size is positively related to the adoption of new technologies including soil conservation (Nowak, 1987), integrated pest management (Thomas et al., 1990) and modern irrigation (Dinar et al., 1992). This may be due to the better ability of big farms to hire crop consultants, easier access to credit and information, and increased contacts with representatives of extension agencies and agribusiness.

Lack of success stories:

There have been no success stories of precision farming to date under Asian conditions. In order for farmers to adopt the technologies with confidence, they need to see the value of adoption.

Heterogeneity of cropping systems and market imperfections:

Farm units in Asia are highly heterogeneous and the costs and benefits of adoption vary across widely. Further, market imperfections such as distortions in input and output markets, institutional hurdles to efficient input application, prices that do not reflect their true scarcity values, and absence of penalties for residual generation lessen the potential benefit of adoption. Because of high subsidies, the cost of fertilizers and pesticides is so low in Japan that saving on inputs cannot be a major incentive to adopt precision farming.

Land ownership, infrastructure and institutional constraints:

In Japan, adoption of precision farming is hampered partly by restrictions on land ownership by the private sector. In developing countries of Asia, policy and bureaucratic constraints slow down the process of timely information transfer. Further, poor coordination among the private sector, research and administration agencies makes the adoption of these technologies slower. The slow diffusion can also be due to the small number of input dealers offering such services to growers.

Lack of local technical expertise:

Adoption of precision farming requires a relatively advanced and computer literate workforce. In Hokkaido, which is nearly equal in area and population to Austria and Denmark respectively, only 4-5 people are working on integration of remote sensing, GIS and GPS. This shows a severe shortage of skilled manpower. Moreover, the learning costs of adoption of precision farming are influenced by variations in personal ability and age of farmers, motivation, quality and number of years of education, and exposure to extension services. Because Asian farmers lack enough exposure to data management technologies, they have to rely on farm consultants. It is, therefore, unlikely that precision farming will be adopted soon if governments and private associations do not make additional efforts.

Knowledge and technological gaps:

Inadequate knowledge of the user needs and poor understanding of researchers to tackle major grower concerns are important constraints. For instance, very few crop growth models are directly applicable to the concurrent management of the varied growing conditions in Asia. Studies to improve capacity for quantitative modeling of agricultural systems are, therefore, necessary. Other constraints include gaps in communication between computer users and data suppliers, and between growers and the precision farming industry (Maji et al., 1997). Accurate analysis of farm data is another weak link in the spread of these technologies. It is not always possible to identify relationships between variability in yield and variability in measured factors because the former results from multiple interactions among the environment, management, genetics, and biotic and abiotic stresses, which vary across a field. In some soils of Hokkaido, P status was found to be highly variable but there was no response to variably applied P because those areas probably had other problems with pH, lime content, organic matter, soil depth and/or water holding capacity.

Data availability, quality and costs:

Difficulties in obtaining reliable data in a timely and cost effective way are limiting the adoption of precision farming in Asia. For example, most available data from public agencies in Hokkaido extends over many districts. If data are made available for an area of single agricultural association or a municipality, people may receive the idea of precision farming more enthusiastically. High price of imagery has also been the biggest obstacle in routine use of such data.

Despite the many obstacles listed above, business opportunities for precision farming technologies including GIS, GPS, remote sensing, and yield monitor systems are immense in Asia. The scope for founding new hardware, software and consulting industries related to precision agriculture is gradually widening. In Japan, the market in the next five years is estimated at about US$ 100 billion for GIS, and about US$ 50 billion for GPS and remote sensing (Machida, A., personal communication). Of this, the agricultural market size is considered reasonably large. Within each Asian country, however, some regions are in a better position than others to adopt precision farming. In Japan, Hokkaido is better placed than other prefectures because of its relatively big farms. Punjab and Haryana states in India, where farm mechanization is more common than in others, may be the first to adopt precision farming on a large scale.

Recently, the governments of certain Asian countries initiated special efforts to promote precision farming. In Japan, the Ministry of Agriculture has allocated special funds for research on remote sensing applications of precision farming. A quasi-governmental institute "Bio-oriented technology Research Advancement Institution (BRAIN)" is also funding research on precision farming (Kobayashi, M., personal communication). In Malaysia, the Malaysian Agricultural Research and Development Institute (MARDI) is promoting research on precision farming of upland rice (Mohamed, A.Z., personal communication). In other countries, the private sector, which holds or leases a large acreage, is likely to adopt precision farming sooner than the smallholders.

Precision farming is useful in many situations in Asia but only a few priority topics will be discussed here in detail. Rice, wheat, sugar beet, onion, potato, and cotton among the field crops, and apple, grape, tea, coffee and oil palm among horticultural crops are perhaps the most relevant. Some have a very high value per acre, making excellent cases for site specific management. For all these crops, yield mapping is the first step to determine the precise locations of the highest and lowest yield areas of the field, and to analyze the factors causing yield variation. Testing of precision farming technologies for paddy rice at the research farm level is in progress at Kyoto, Tokyo and Hokkaido universities. Researchers at Kyoto University recently developed a two-row rice harvester for determining yields on a microplot basis (Iida et al., 1998).

Precision farming can bring several benefits to the sugar beet industry in Hokkaido, where the marketing system was changed in 1986 from a quantity (fresh weight) to quality (sugar yield) basis. Heavy N fertilization, a common practice here, results in excessive N levels and a decreased sugar concentration. It is now possible to estimate sugar and amide N concentration of leaves using reflectance in visible bands, and root yield using reflectance in visible and infrared bands (Okano et al., 1997). Incorporation of such data into a GIS along with precise positioning of non-uniform areas using GPS can be used to vary fertilizer dose within a field, thereby improving productivity. Although weighing conveyor technology has been known for some time, effective yield measurement still remains the main problem in crops such as sugar beet, onion and potato. Further, the preparation of product quality maps for these crops is as important as yield maps. In India, a few researchers in the private sector initiated studies on precision agriculture in high value crops like cotton, coffee and tea. In cotton, remote sensing coupled with GIS can assist in improved precision of insect pest management and harvesting. In Sri Lanka, researchers at the Tea Research Institute are examining precision management of soil organic carbon (Anandacoomaraswamy and Ananthacumaraswamy, 1998).

Insofar as dairy farming in Asia is concerned, precision farming techniques can help in improving efficiency of methods, timing, and rate of application of animal wastes leading to high application efficiency and low environmental pollution while considering soil and climatic conditions. For instance, factors determining the risk of nitrate leaching, release of N₂O through denitrification and contamination of surface and ground waters by runoff can be mapped and analyzed. Likewise, poorly managed areas in grasslands can be identified and the optimum period for cutting on a plot basis determined.

Nutrient stress management is another area where precision farming can help Asian farmers. Most cultivated soils in Japan are acidic and spatial variation in pH is high. Detecting nutrient stresses using remote sensing and combining data in a GIS can help in site-specific applications of fertilizers and soil amendments such as lime, manure, compost, gypsum, and sulfur, which in turn would increase fertilizer use efficiency and reduce nutrient losses (Sawyer, 1994). In semi-arid and arid tropics, precision technologies can help growers in scheduling irrigation more profitably by varying the timing, amounts and placement of water. For example, drip irrigation, coupled with information from remotely sensed stress conditions (e.g., canopy temperature), can increase the effective use of applied water from 60 to 95%, thereby reducing runoff from 23 to 1%, and deep percolation from 18 to 4% (Hanemann et al., 1987).

Pests and diseases cause huge losses to Asian crops. If remote sensing can help in detecting small problem areas caused by pathogens, timing of applications of fungicides can be optimized. Recent studies in Japan show that pre-visual crop stress or incipient crop damage can be detected using radio-controlled aircraft and near-infrared narrow-band sensors. Likewise, airborne video data and GIS have been shown to effectively detect and map blackfly infestations in citrus orchards, making it possible to achieve precision in pest control (Everitt et al., 1994). Perennial weeds, which are usually position-specific (Wilson and Scott, 1982) and grow in concentrated areas, are also a major problem in Asian countries. Remote sensing combined with GIS and GPS can help in site-specific weed management.

Although thorough cost-benefit analysis has not been done yet, the possible use of precision technologies in managing the environmental side effects of farming and reducing pollution is appealing. For instance, environmental law in Japan prohibits applying certain pesticides and herbicides within a specified distance of a stream or water body. In such cases, precision farming technologies can help growers apply pesticides in a safer manner by using GPS along with a digital drainage map. The technologies need not be limited to input application. They can be used in (a) implementing spatially-varied farm operations such as tillage, seeding, harvesting, etc., (b) on-farm testing of agronomic practices to evaluate alternative management practices, (c) plant breeding programs to test the performance of improved varieties, and in (d) re-evaluations of trial procedures.

Precision farming is still only a concept in Asia and strategic support from the public and private sectors is essential to promote its rapid adoption. Successful adoption, however, comprises at least 3 phases including exploration, analysis and execution. Data on crop yield, soil variables, weather and other characteristics are collected and mapped in the exploratory stage, which is important for increasing the awareness among farmers of long term benefits. The approaches to data collection and mapping must, therefore, reflect local needs and resources. For instance, soil sampling on a grid basis can provide the most accurate guide for variable rate application, but it is prohibitively expensive for most farmers in Asia. In such cases, sampling can make use of other information such as past field history, yield maps, and remote sensing as guides to reduce the number of soil sampling sites. Additional research is also necessary on various criteria for indicating spatial patterns in crop yield and fertility. Mulla and Bhatti (1997) reported that variability in wheat yield was a sensitive indicator of spatial patterns in fertilizer requirements of N, but not P. In contrast, the variability in surface organic matter content was moderately sensitive to variations in N requirements, and highly sensitive to variations in P requirements.

In the analysis stage, factors limiting the potential yield in various areas within a field and their interrelationships are examined using GIS-based statistical modeling. Sadler et al. (1998) showed that quantitatively important yield variation may occur over distances as short as 10 m. However, only some factors such as soil structure, water status, pH, nutrient levels, weeds, pests and diseases, etc. can be controlled but not the others (soil texture, weather, topography, etc.). After determining the significance of each source of variability to profitability of a particular crop and relative importance of each controllable factor, management actions can be prioritized. It must be remembered that in some low yielding areas, the reason for poor yields may be the lack of sufficient soil nutrients in the first place. In such cases, application beyond just replenishment is necessary.

Variable application of inputs or cultural operations comprises the execution phase. In most developing countries of Asia, however, it is not always necessary and/or possible to use variable rate applicators. Efforts must, therefore, initially focus on limiting indiscriminate use of inputs in conventional methods. Once the economic and environmental benefits are known widely, variable rate technology would be rapidly implemented at least in high value crops.

To spur adoption of precision farming methods in Asia, pilot demonstration projects must be conducted at various growers’ locations by involving farmers in all stages of the project. The pilot projects must attempt to answer the grower’s needs and emphasize the operational implementation of technology and complete analysis of the costs and savings involved. Documentation of pilot projects would help in examining the operational weaknesses and identification of remedial measures. The projects can be used to train innovative farmers and early adopters, expose the neighboring non-participating farmers to the new technologies, and show the usefulness of the technology for short- and long-term management. Based on these projects, the extension agencies can gather and convey success stories to the public in other regions.

The role of agricultural input suppliers, extension advisors, and consultants in the spread of these technologies is vital. For instance, public agencies should consider supplying free data such as remotely sensed imagery to the universities and research institutes involved in precision farming research. Also, professional societies of agronomy, agricultural informatics, and engineering must provide training guidance in the use of technologies. The involvement of interdisciplinary teams is essential in this. Small farm size will not be a major constraint, if the technologies are available through consulting, custom and rental services. For instance, by renting the equipment, manufacturers can enable early adapters to avoid the risks associated with purchasing costly machinery.

The role of agricultural cooperatives is important in dissemination of precision farming technologies to small farmers. If precision farming is considered a series of discrete services: map generation, targeted scouting, etc., it is possible to fit these services within the structure of a progressive agricultural cooperative in each Asian country. For example, in Japan, most farmers are not yet ready to make big investments in precision farming even if technology is convincing, mainly due to small farm size. However, most farmers belong to JA (Japan Agricultural Cooperative), a national organization linked through 2,472 primary cooperatives that provide five types of services including financial guidance, marketing and supply, credit, welfare and insurance (Table 5). If JA groups can implement precision farming in selected regions and cropping systems by involving the private sector, the spread of technology will be rapid. For instance, satellite imagery can be acquired for the entire region of a primary society and the costs may be distributed to individual farmers. In addition, agricultural associations can assign some funds to increase farmer awareness of the value of precision farming. In Japan, lifting restrictions on land ownership by private agribusiness may also help in rapid implementation of precision farming.

Changes in agricultural policies are also necessary to promote the adoption of precision farming. There are basically two policy approaches: regulatory policies, and market-based policies. The former refer to environmental regulations on the use of farm inputs, and the latter refer to taxes and financial incentives aimed at encouraging growers to efficiently utilize farm inputs. In most Asian countries, the lack of penalties for pollutant generation has partly contributed to an excessive use of inputs. Subsidies on inputs and outputs, and mechanisms that prevent the price system from rationing limited resources are also common. The latter include state-guaranteed crop prices, tariffs, import quotas, export subsidies, etc. Inputs such as water and fossil fuels are usually sold at prices that are well below the real resource cost of their use, which consists not only production costs but also includes scarcity value and costs of pollution. In such cases, the formulation of policies that reflect the real scarcity value of natural resources and penalize pollution, and policies such as green payments for farmers adopting techniques that would lower environmental costs can promote the adoption of precision farming technologies (Branden et al., 1994).

Table 5. Organizational structure of JA

Type of service	JA Group Level
	national	prefectural	local
Insurance	ZENKYOREN  National Mutual Insurance Federation of Agricultural Cooperatives	KYOSAIREN Prefectural Mutual Insurance Federation of Agricultural Cooperatives	Primary      multi-     functional      agricultural      cooperatives         (2472      societies      with      8.9 million     members)
Guidance	ZENCHU Central Union of Agricultural Cooperatives	CHUOKAI Prefectural Central Union of Agricultural Cooperatives
Marketing and supply	ZEN-NOH National Federation of Agricultural Cooperatives	KEIZAIREN Prefectural Economic Federation of agricultural cooperatives
Credit	NORINCHUKIN Bank Central Cooperative Bank for Agriculture, Forestry and Fisheries	SHINREN Prefectural Credit Federation of Agricultural Cooperatives
Health facilities and Welfare	ZENKOREN National Welfare Federation of Agricultural Cooperatives	KOSEIREN Prefectural Welfare Federation of Agricultural Cooperatives

Source: http://www.zenkyoren.or.jp/e/e-page/jagrp.htm

In most Asian countries, the pollution effects of agriculture have been largely ignored so far because of inability to effectively monitor such effects. The advent of precision farming, and the computerization of input and output flows, will now enable such monitoring. Higher taxes on polluting farms are often recommended, but there is strong opposition to the implementation of the Polluter-Pays-Principle concept in most countries including Japan. At the same time, some consumers in Japan would like to see a drastic reduction in the use of pesticides and fertilizers, and are willing to pay as much as 4-6 times the normal price for produce such as organic vegetables, soybean and wheat. When the price elasticity of input use is low and the input costs are only a small part of the total production expenditures, as in the case of fertilizers and pesticides, very high taxes are required to reduce their use adequately. Given the unfeasibility of such high taxes, a hybrid policy may be implemented for controlling pollution. A tax-free quota of N can be combined with taxes on additional N use (Dubgaard, 1990).

At the research level, many issues remain to be resolved. Although some progress has been made at Kyoto University, yield monitors for small farm conditions are yet to be developed. The development of standards for the hardware and software (image transfer formats and GPS transfer formats, map projection formats) is another issue. Crop models and decision support systems must be improved by considering local resources. Data for calibration of models must be made available to increase their accuracy and/or predictability.

The ability to finance a creative information venture in agriculture will affect the speed of diffusion of precision farming technologies. Commercial banks, as well as other sources of funding, have to be educated regarding the potential of precision farming. In many Asian countries, it may be worthwhile to develop programs of subsidized credit to enable R&D activities on precision farming.

Precision farming in Asia is in its infancy but there are numerous opportunities for adoption. I believe that progressive Asian farmers, with guidance from the public and private sectors, and agricultural associations, will adopt it in a limited scale as the technology shows potential for raising yields and economic returns on fields with significant variability, and for minimizing environmental degradation. Although it is recognized that agriculture is a major polluter of the environment in many Asian countries, farmers will not adopt precision farming unless it brings in more or at least similar profit as compared to traditional practice. The support from governments and the private sector during the initial stages of adoption is, therefore, vital. It must be remembered that not all elements of precision farming are relevant for each and every farm. For instance, introduction of variable rate applicators is not always necessary or the most appropriate level of spatial management in Asian farms. Likewise, not all farms are suitable to implement precision farming. Some growers are likely to adopt it partially, adopting certain elements but not others. Precision farming cannot be convincing if only environmental benefits are emphasized. On the other hand, its adoption would be improved if it can be shown to reduce the risk. We must be cautious, however, in not overselling the technologies without providing adequate product support. The adoption of precision farming also depends on product reliability, the support provided by manufacturers and the ability to show the benefits. Effective coordination among the public and private sectors and growers is, therefore, essential for implementing new strategies to achieve success.

I wish to thank Y. Komata, G. Matsuda and K. Ackermann for their help in preparation of this manuscript.

Abrol, I.P. 1998. Sustaining rice-wheat cropping system productivity in the Indo-Gangetic plains. p. 155-165. In Sustainable agricultural development compatible with environmental conservation in Asia. Proc. Fourth JIRCAS Int. Symp. Tsukuba, 18-22 Sep. 1997. JIRCAS, Tsukuba, Japan.

Anandacoomaraswamy, A. and S. Ananthacumaraswamy. 1998. Precision management of soil organic carbon in tea lands of Sri Lanka. p. 71. In Abstracts of the Fourth Int. Conf. Precision Agriculture, July 19-22, 1998. St. Paul, MN.

Branden, J.B., N.R. Netsusil, and R.F. Kosobud. 1994. Incentive-based non-point source pollution abatement in a re-authorized clean water act. Water Resources Bull. 30(5):781-791.

Byerlee, D. 1994. Modern varieties, productivity, and sustainability: Recent experience and emerging challenges. CIMMYT, Mexico D.F., Mexico.

Changyao, W. 1995. Remote sensing monitoring on land use change in China. p. 20-26. In Vegetation Monitoring. Proc. Int. Symp. 29-31 Aug. 1995. Ctr. Environ. Remote Sens., Chiba Univ. Chiba, Japan.

Dinar, A., M.B. Campbell, and D. Zilberman. 1992. Adoption of improved irrigation and drainage reduction technologies under limiting environmental conditions. Environ. Resources Econ. 2(4):360-373.

Dubgaard, A. 1990. The need for a common nitrogen policy in the EC. p. 131-136. In R. Calvet, (ed.) Nitrates-Agriculture-EAU. Int. Symp., Paris, Nov. 7-8, 1990. INRA, Paris, France.

Everitt, J.H., D.E, Escobar, D.E., K.R. Summy, and M.R. Davis. 1994. Using airborne video, global positioning systems and geographic information system technologies for detecting and mapping citrus blackfly infestations. Southwestern Entomol. 19(2):129-138.

Garcia, P.P., N. Ito, K. Kito, and X.L. Wang. 1998. Computer-based optimal control of seeding rate based on travel speed and seed signals. J. Japanese Soc. Agric. Machin. 60(3):79-86.

Hanemann, W.M., E. Litchenberg, D. Zilberman, D. Chapman, L. Dixon, G. Ellis, and J. Hukkinen. 1987. Economic implications of regulating agricultural drainage to the San Joaquin river. Western Consortium for the Health Professions, Inc., San Francisco, CA.

Hatanaka, T., A. Nishimuna, R. Nira, and M. Fukuhara. 1995. Estimation of available moisture holding capacity of upland soils using Landsat TM Data. Soil Sci. Plant Nutr. 41(3):577-586.

Hokkaido Department of Agriculture. 1998. Agriculture in Hokkaido 1998-99. pp. 30. Dept. of Agric., Hokkaido Pref. Gov. Sapporo, Japan.

Iida, M., M. Umeda, T. Kaho, C.K. Lee, and M. Suguri. 1998. Measurement of grain yield in Japanese paddy field. p. 54. In Abstracts of the Fourth Int. Conf. Precision Agriculture, July 19-22, 1998. St. Paul, MN.

Inoue, Y. 1998. Application of remote sensing to information-based precision farm management. Journal of the Japanese Society of Agricultural Machinery 60(3):141-150.

Japan Agricultural Software Association, 1996. Agriculture-related software book. (In Japanese). Rakuyu Shobo Inc. Tokyo, Japan.

Larscheid, G. and B.S. Blackmore. 1996. Interactions between farm managers and information systems with respect to yield mapping. p. 1153-1163. In P.C. Robert et al., (ed.) Precision Agriculture. Proc. Third Int. Conf. Minneapolis, MN. June 23-26, 1996. ASA, CSSA, SSSA, Madison, WI.

Maji, A.K., G.S. Sidhu, B.K. Kandpal, S. Pande, M. Velayudham, and M.I. Ahmed. 1997. Evaluation and Management of Rice-wheat cropping systems in Indo-Gangetic Plains using GIS. In Use of GIS in analysis of cropping systems, Training Workshop, Patancheru. 20-29 Aug. 1997. ICRISAT, Patancheru, India.

Mino, N., G. Saito, and S. Ogawa. 1998. Satellite monitoring of changes in improved grassland management. Int. J. Remote Sens. 19:439-452.

Ministry of Agriculture. 1996. Agricultural statistics at a glance. Directorate of Economics and Statistics. Dept. Agric. Coop., Gov. India. New Delhi, India.

Mulla, D.J. and AU. Bhatti. 1997. An evaluation of indicator properties affecting spatial patterns in N and P requirements for winter wheat yield. p. 145-154. In J.V. Stafford (ed.), First European Conf. Precision Agric. 7-10 Sep. 1997. BIOS Sci. Publ., Oxford, UK.

Nowak, P.J. 1987. The adoption of agricultural conservation technologies: economic and diffusion expectations. Rural Sociol. 52(2):208-220.

Okamoto, K., M. Fukuhara, and T. Hatanaka. 1990. Mapping method of soil organic matter content of Obihiro area with a Landsat TM data. (in Janapese with English summary). J. Jpn. Sci. Photogramm. Remote Sens., 29(6):45-52.

Okano, C., A. Nishimune, M. Fukuhara, K. Okamoto, and M. Hayasaka. 1997. Sugar beet nutritional diagnosis using remote sensing. p. 381-382. In T. Ando et al. (ed.) Plant Nutrition for sustainable food production and environment. Kluwer Acad. Publ., Tokyo, Japan.

Okano, C., K. Okamoto, M. Fukuhura, and A. Nishimune. 1995. Crop maps and yield maps of sugar beets in the Tokachi Plains, Japan, developed from multi-temporal Landsat TM data. p. 275-281. In Vegetation Monitoring. Proc. Int. Symp. 29-31 Aug. 1995. Ctr. Environ. Remote Sens., Chiba Univ. Chiba, Japan.

Sadler, E.J., W.J. Busscher, P.J. Bauer, and D.J. Karlen, 1998. Spatial scale requirements for precision farming: A case study in the Southeastern USA. Agron. J., 90:191-197.

Sawyer, J.E. 1994. Concepts of variable rate technology with considerations for fertilizer application. J. Prod. Agric. 7(2):195-201.

Shibasaki, R., M. Takagi, and K. Iwao. 1995. Land use change study for South East Asia. p. 199-205. In Vegetation Monitoring. Proc. Int. Symp. 29-31 Aug. 1995. Ctr. Environ. Remote Sens., Chiba Univ. Chiba, Japan.

Shibata, Y., K. Nishizaki, Y. Yokochi, A. Karaushi, and K. Araki. 1998. Basic studies on weeding without herbicide – continuous recognition system. J. Jpn. Soc. Agric. Machinery 60(3):87-95.

Shiga, H. 1997. Evaluation of land productivity by combination of satellite data, soil information and meteorological information. Hokkaido Pref. Agric. Exp. Stn. Rep. No. 91. Hokkaido Central Exp. Stn., Naganuma, Japan.

Tanaka, A. 1997. Systemic production of horticultural plants by microcomputers. III. Operation with LAN system for a production organization. (In Japanese). Agric. Info. Res. 6(1): 9-25.

Thomas, J.K., H. Ladewig, and W.A. McIntosh. 1990. The adoption of integrated pest management practices among Texas cotton growers. Rural Sociol. 55(3):395-410.

Wilson, B.J., and J.L. Scott. 1982. Population trends of Avena fatua and Alepecuras myosurooides on commercial arable and dairy farms. p. 619-628. In Weeds, Proc. British Crop Prot. Conf. SCI, London, UK.

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