A MOBILE APPLICATION SYSTEM FOR SUSTAINABLE AGRICULTURAL DEVELOPMENT IN BANGLADESH

Bangladesh J. Agri. Engg. 24(1&2) 45–51: 2013

A MOBILE APPLICATION SYSTEM FOR SUSTAINABLE AGRICULTURAL DEVELOPMENT IN BANGLADESH Nashid Alam1 and Asma-Ull-Hosna2

ABSTRACT Bangladesh faces numerous challenges that hinder the ability of the agricultural sector to develop to its full economic potential. Most of these challenges can be controlled through expert advices to grass-root farmers. Several studies have addressed problems, but the outcomes have not been put into practice. This study shows how solutions can be created using mobile phone technology that will help to address some of the problems faced by the farmers. Here, a set of farmer friendly services is addressed to bridge the existing gap between agro-science experts and farmers living in remote areas. The paper also presents the benefits Bangladeshi farmers receive from using “Robi Mobile Shayba” service, mobile phone technology developed by agricultural experts working for Robi Axiata Ltd. The benefit of using this application has been analysed by cost-benefit ratio. It is suggested that a design model for such applications can be adopted by software developers in near future.

INTRODUCTION It is estimated that world food production needs to increase by 70 per cent by 2050 (Cribb and Julian, 2010). The agricultural community in Bangladesh is urgently aiming to promote sustainable agriculture in the public and private sectors. Researchers have embarked on different paths to sustainability, incorporating innovative approaches (USDA, 1999). New mechanisms to foster development and diffusion of innovation are needed to strengthen the ways in which information; knowledge and technology are developed and disseminated to ensure the global changes benefiting farmers, food insecure households and other vulnerable groups (Anandajayasekeram et al., 2008). Farmers do not know when and how to apply what fertilizers and pesticides, what crops to grow with the main crops; and side-businesses. Some of these problems can be tackled using mobile phones. In the developing world, the main concerns are soil depletion, water scarcity and habitat loss due to over-cropping, over-grazing and deforestation (OECD, 2008). Farmers often face intermittent availability of water, especially in the night. The main technical constraints to agricultural production are lack of infrastructure, unfavourable land policies, poor climate and pests and diseases (Langyintuo et al., 2008). There is a large gap between scientific knowledge available and its practical application. A recent study using option value models has investigated agricultural investments to understand why technology adoption rates are slow (Baerenklau and Keith, 2007). Some issues, such as irregular monsoons and insufficient rainfall can not be addressed. But there are problems that can be solved with proper advice. Farmers can be advised about alternative water sources, procurement of affordable fertilizers and pesticides, and details of Lecturer, Department of Computer Science and Engineering, Sylhet Agricultural University, Sylhet-3100, Bangladesh 2 Lecturer, Department of Computer Science and Engineering, Stamford University Bangladesh, Dhaka-1000, Bangladesh 1

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funding agencies with comparison of loan repayment options. They can be empowered to supply products avoiding middle-men. They can acquire skills such as how to maximize yield by growing compatible crops, along with the main ones, crop rotations depending on the location and soil (Joshi and Tyagi, 1994). The difference in the use of digital technology between rural and urban areas in Bangladesh is slowly decreasing and farmers are getting familiar with mobile and internet applications. However, there is no comprehensive report on the application of these techniques to the specific needs of farmers. Nokia’s Ovi Life Tools (OLT) is a platform for agricultural mobileapplication providers. OLT has a large user base in developing countries including Bangladesh. An alternative platform, still in its beta phase, is “BlueVia” from Spain’s Telefonica. BlueVia (http://www.bluevia.com/about/) is similar to OLT in terms of platform functions, but mobile-application providers only have access to Telefonica subscribers because the platform is not integrated with competing mobile network operators. This study is designed to develop a suitable telecommunication system using mobile phone for sustainable agricultural development in Bangladesh.

MATERIALS AND METHODS A wide range of services were provided to the farmer through the Gram Panchayat (local government) who are closely associated with the farmers. These services were personalized, meaning the information appearing on the user interface were relevant to the farmer using the application, achieved by capturing the location of the farm, so that data relevant to that location were given. The services are as follows: Registration service The details captured were farmer’s land location details, soil type, crops grown, amount invested by the farmer for seeds, pesticides and fertilizers in last three years, the crop yield, income or loss incurred for each crop. The registration service’s working procedure is shown in Fig.1.

For providing personalized service

History data gathering service

Registration service New farmer

Offline document verification of farmer

Fig.1 Depicting the registration service

Farmer Id given after verification

Gram Panchayat (local government)

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Yield prediction service A multiple regression model (Bruce and William, 2003) with many independent variables was used where data was utilized to identify relationships among variables. These relationships were used for predictions. The following predictions were done based on soil profile (soil type, nutrients present) and land profile (land area and location). a) The investment on fertilizers and seeds for a given soil and land profile, to get ‘percentage yield, ‘n months later, for a specific crop; b) The yield, for a farmer’s soil and land profile with the amount of fertilizers and pesticides applied; c) A comparative analysis of the yield for a particular soil and land profile, if different crops are cultivated. Crop monitoring service is depicted in Fig.2.

Yield prediction service Personalized prediction

Gather data E.g.: Investment amount for seeds/sapling, pesticides, fertilizers, amount of land cultivated

Registered farmer or Gram Panchayat user

Fig.2 Depicting the crop monitoring service

Market and storage locator service Market and storage services were used to locate local and export markets, near the farm for the farmer to sell and store his/her produce hygienically, avoiding corrupt chain of middlemen. Fig. 3 shows the market and storage locator service.

Export market service Personalizes search gives information with respect to farmer’s land location facilities

Search for information

Local market service

Storage finder service

Fig.3 The market and storage locator service

Registered farmer or Gram Panchayat user

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This service aims to bridge the gap between the vast amounts of knowledge with agricultural scientists. As shown in Fig.4, personalized advice is given on crop rotation, amount of pesticides and fertilizers to use, methods of preparation of land, alternative crops that can be grown alongside the main crops or during the period between crop growing seasons, and side-businesses that can be adopted to augment profits. Agriculturalists of Robi Axiata Ltd. advised growing the fruit crop sobeda (Manilkara zapota, or sapodilla) in Rampal Upazila (Sub-district) of Bagerhat District in the Division of Khulna. These farmers were associated with the extension worker from 2011. The local soil of Rampal is sandy. Red soil was mixed to the native sandy soil to increase the quality. Expert active service

Agriculture expert

Advice suggested are: 1. Crop rotation strategies

Registered farmer or Gram Panchayat user

2. Alternate crops to grow with the main crops 3. Side business that help maximize profit 4. What pesticides and fertilizers to use

Fig.4 The expert advice service

Crop monitoring service In this service, agricultural experts viewed the various stages of crop cultivation from preparation of the cultivable land through pictures uploaded from the mobile application. As shown in Fig.5, the pictures of the crop allowed the experts to impart better advice, and eliminate the need for the agricultural experts to visit the land. Crop monitoring service

Agriculture expert

A personalized advice service for the farmers. The farmers’ crops are monitored by taking their pictures and uploading the same to be reviewed by the expert. Case study 1: Disease of the crops can be reviewed timely relevant measures can be taken on the expert’s advice. Case study 2: Periodic checks on the growth of the crop can be monitored remotely and advice given to improve yields. Fig.5 Using cases for the crop monitoring service

Registered farmer

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RESULTS AND DISCUSSION Face-to-face expert advice Table 1 shows the benefits of getting face-to-face expert advice from the agriculturalists of Robi Axiata Ltd. The advantages of this collaboration were seen in 2012, when the sobeda trees started giving fruit. The agricultural experts categorized the soil into Rain-fed (RF) and Irrigated Dry (ID), red loamy-RF, red sandy-RF, red loamy soil-ID and red sandy soil-ID. As shown in Table 1, the best soil for growing Sobeda was red loamy soil-RF. But, since the native soil of Rampal was sandy, the land was prepared by adding red soil. The monsoons are moderate in that part of the village, so they chose to depend on Rain-fed (RF), keeping cultivation cost under control. Advice was given on measures to prevent damage due to pests, soil nutrient management during water-logged and drought conditions, steps to take during high or low temperature and humidity, amount of micro-nutrients (zinc, magnesium, iron, gypsum) were added during various stages of the Sobeda sapling’s growth, and pheromone traps for attracting male insects to reduce damage to fruit. Table 1: Expenditure and benefit for crop production using “Robi Mobile Shayba” service Soil type and condition (RF/ID) Red Loamy Soil-RF Red Loamy Soil-ID Red Sandy Soil-RF Red Sandy Soil-ID

Without expert advice

With expert advice

Cultivation cost (Taka)

14000-23000 12000-18000 10000-15000 8000-12000

19000-27000 16000-23000 14000-20000 13000-17000

4000-6000 6000-8000 6000-8000 8000-10000

Yield (kg/acre)

In East Asia, a 10 per cent growth in cereal yields was accompanied by a decline in rural poverty of more than 53 per cent. In Eastern Europe and Central Asia, after a transition over which yields were stagnant and poverty rose, subsequent yield gains were associated with a rapid decline in rural poverty. In Latin America and the Caribbean, cereal yields grew at an average annual rate of 2.5 per cent, yet rural poverty hardly decline. Clearly, the way yield gains achieved did not help reduce poverty. In Sub-Saharan Africa, yields were largely stagnant and the rural poverty rate remained unchanged. Similar patterns are observed at the country level, with elasticities of rural poverty reduction with respect to cereal yield growth equal to 25.1 in China, 21.2 in India, and 20.6 in Brazil (Bussolo and O’Connor, 2002). These are simple correlations, yet the contrast is telling of how land productivity gains can reduce rural poverty. The China-Brazil contrast reveals the importance of a more egalitarian land tenure system in transmitting productivity gains into poverty reduction (de Janvry et al., 2010). The factors hindering the establishment of a competitive distribution network were poor roads, especially during the rainy season, and poor storage systems. The bad roads drive up the cost of seed (Langyintuo et al., 2008). Expected outcome of online expert advice An elementary estimate about the benefits of expert advice is shown below: Average extra yield per acre = 4000 kg Price per quintal = Tk.900/- per kg Extra benefit per acre = 4 × 900 = Tk.3600/-

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50 Average size of the farm = 5 acres Extra benefit per farmer = 5 x 3600 = Tk.18000/Extra benefit for 1000 farmers = Rk.180,00,000 (Tk.180 Lacs)

Consider a case where the 1000 farmers were aided by five extension experts, 20 cooperative society personnel, computers, mobile phones, digital cameras. A rough estimate of this budget was Tk.120 Lacs, out of which approximately Tk.90/= Lacs is the cost of the equipment and software (http://calc2013.costs.infomine.com/). If the equipment costs were spread over a period of two years, the cost of equipment per year comes to Tk.45 Lacs. Total expenditure per year = Working expenses + Equipment cost, Tk.30/= Lacs + Tk.45/= Lacs = Tk.75/= Lacs. Overall net benefit per year = Extra economic benefit – System cost, Tk.180/= Lacs – Tk.75/= Lacs = Tk.105/= Lacs per year. Benefits/cost rations: Benefits (B) - Advantages to the owner (The owner may be the public) Disbenefits (D) - Disadvantages to the owner when the project under consideration is implemented. Costs (C) - Anticipated expenditures for construction, Operation and Maintenance, Etc. Benefits − Disbenefits Costs If B/C > 1.0 then the project is advantageous. B, C and D must all be in same taka units – PW, FAC or FW B/C =

Costs are not negative. Modified B/C = =

Benefits – Disbenefits – M & O costs Initial investments - salvage Net benefits Net cost

1st cost: PW = Tk.3,000,000 + Tk.4,000,000 (P/F, 20) = Tk.4,507,600 Relining cost: PW = Tk.160,000 (P/F, 10+20) + Tk.320,000 (P/F, 5, 30+40) = Tk.160,000 (0.9908) + Tk. 320,000 (0.3734) = Tk.278,016 Note: (P/F, 5, 10 + 20) = (P/F, 5, 10) + (P/F, 5, 20) Benefits PW = Tk.260,000 (P/A, 5, 20) + Tk.3000,000 (P/A, 5, 30) (P/F, 5, 20) = Tk.260,000 (12.4622) + Tk.300,000 (15.3725) (0.3769) = Tk.4,978,340 B/C =

4,978,340 = 1.040 4,507,600 + 278,016

Modified B/C =

4,978,340 – 278,016 = 1.042 4,507,600

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The research is justified in either case, since B/C>1.0 Note that if the B/C ratio is greater than 1.0, the modified B/C will also be greater than 1.0.

CONCLUSIONS Tasks were accomplished with regards to gathering the requirements and developing a prototype model of the five farmer friendly services are described. With the help of Robi Axiata Ltd., this study is deployed in the Rampal village in Bagerhat district, where the field work was done through the farmer friendly service using the IBM Smart Cloud Platform in both web and mobile clients. An appropriate data mining tool will be used to decrease the response time to process the large current and history data. One of the major issues faced by the farmers is intermittent availability of water, many a time in the middle of the night. Our cloud based application tasks could be used to solve this problem.

ACKNLOWLEDGEMENTS The authors are very much grateful to Dr. William R Ward, University of Liverpool, UK for his help in preparing the manuscript.

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