Information and communication technologies (ICTs) have always mattered in agriculture too. In day-to-day practices of agriculture and allied sectors, the farmers often share their information. Changing weather patterns, soil conditions, pests and diseases always throw challenges to small and marginal farmers. So, the farmer needs up-dated information to cope with and even benefit from these changes. In the developing countries like India, where agriculture still plays a crucial role (over 58% of the rural households depend on agriculture as their livelihood) and the rising population from 1027 million to 1419 million during 2001-16 (a total rise of 38 percent or 1.3 percent per year) pose a lot of pressure on land and other resources to meet the food security needs on one hand and to meet the challenges of globalization on the other. Understanding and addressing these challenges are very crucial, in which ICT can play a major role. With the booming mobile, wireless, and Internet industries, ICT has found a foothold even in poor marginal and smallholder farms and in their activities. The survey conducted among the 120 farmers in Srikakulam district in India revealed that, ICT has revolutionized the agriculture in the modern days. Production and marketing information is accessed by 91% of the sample farmers through mobile in 2015, where it was only 5% in 2005. The extent of use of mobile phones by the farmers varied with the decision to be taken by them like Harvesting, packing, and storing (94%), Selling Decision (91%), Seed purchase (89%), Application of fertilizers and pesticides (88%) and Land preparation and planting (84%), other package of practices (77%). The farmers further opined that, ‘Voice’ was the dominating source of communication (96%) compared to Short Message Service (SMS) (only 27%) and Internet access (10%), as majority are illiterate. The use of camera (71%), Bluetooth (33%), Radio (61%) TV (41%) are the other means of sharing the information. In this context of importance of ICTs in Indian agriculture, greater attention justifies about the applications of ICT’s to alleviate poverty and promote economic growth of the farming population.

This paper presents how Digital Knowledge Ecosystem such as “Govi Nena” (translates as agriculture intelligence) can be used to provide a more effective and practical solution to eliminate the inefficiencies in agricultural markets and achieve higher productivity and price stability. In order to establish the framework to analyze the system, this paper uses a set of hypothetical scenarios faced by value chain actors based on a review of the literature, established knowledge and recent developing country experiences. The scenario analysis reveals that “Govi Nena” enables farmers to make effective production decisions, deepens the level of value chain integration, and enhances the level of welfare for the society as a whole.

India is largest producer of banana in the world producing 29.72 million tonnes from an area of 0.803 million ha with a productivity of 35.7 MT ha-1 and accounted for 15.48 and 27.01 per cent of the world’s area and production respectively (www.nhb.gov.in). In India, Tamil Nadu leads other states both in terms of area and production followed by Maharashtra, Gujarat and Andhra Pradesh. In Rayalaseema region of Andhra Pradesh, Kurnool district had special reputation in the cultivation of banana in an area of 5765 hectares with an annual production of 2.01 lakh tonnes in the year 2012-13 and hence, it was purposively chosen for the study. On 23rd November 2003, the Government of Andhra Pradesh has commenced a comprehensive project called ‘Andhra Pradesh Micro Irrigation Project (APMIP)’, first of its kind in the world so as to promote water use efficiency. APMIP is offering 100 per cent of subsidy in case of SC, ST and 90 per cent in case of other categories of farmers up to 5.0 acres of land. In case of acreage between 5-10 acres, 70 per cent subsidy and acreage above 10, 50 per cent of subsidy is given to the farmer beneficiaries. The sampling frame consists of Kurnool district, two mandals, four villages and 180 sample farmers comprising of 60 farmers each from Marginal (<1ha), Small (1-2ha) and Other (>2ha) categories. A well structured pre-tested schedule was employed to collect the requisite information pertaining to the performance of drip irrigation among the sample farmers and Data Envelopment Analysis (DEA) model was employed to analyze the performance of drip irrigation in banana farms. The performance of drip irrigation was assessed based on the parameters like: Land Development Works (LDW), Fertigation costs (FC), Volume of water supplied (VWS), Annual maintenance costs of drip irrigation (AMC), Economic Status of the farmer (ES), Crop Productivity (CP) etc. The first four parameters are considered as inputs and last two as outputs for DEA modelling purposes. The findings revealed that, the number of farms operating at CRS are more in number in other farms (46.66%) followed by marginal (45%) and small farms (28.33%). Similarly, regarding the number of farmers operating at VRS, the other farms are again more in number with 61.66 per cent followed by marginal (53.33%) and small farms (35%). With reference to scale efficiency, marginal farms dominate the scenario with 57 per cent followed by others (55%) and small farms (50%). At pooled level, 26.11 per cent of the farms are being operated at CRS with an average technical efficiency score of 0.6138 i.e., 47 out of 180 farms. Nearly 40 per cent of the farmers at pooled level are being operated at VRS with an average technical efficiency score of 0.7241. As regards to scale efficiency, nearly 52 per cent of the farmers (94 out of 180 farmers) at pooled level, either performed at the optimum scale or were close to the optimum scale (farms having scale efficiency values equal to or more than 0.90). Majority of the farms (39.44%) are operating at IRS and only 29 per cent of the farmers are operating at DRS. This signifies that, more resources should be provided to these farms operating at IRS and the same should be decreased towards the farms operating at DRS. Nearly 32 per cent of the farms are operating at CRS indicating efficient utilization of resources. Log linear regression model was used to analyze the major determinants of input use efficiency in banana farms. The input variables considered under DEA model were again considered as influential factors for the CRS obtained for the three categories of farmers. Volume of water supplied (X1) and fertigation cost (X2) are the major determinants of banana farms across all the farmer categories and even at pooled level. In view of their positive influence on the CRS, it is essential to strengthen modern irrigation infrastructure like drip irrigation and offer more fertilizer subsidies to the farmer to enhance the crop production on cost-effective basis in Kurnool district of Andhra Pradesh, India. This study further suggests that, the present era of Information Technology will help the irrigation management in the context of generating new techniques, extension, adoption and information. It will also guide the farmers in irrigation scheduling and quantifying the irrigation water requirements in accordance with the water availability in a particular season. So, it is high time for the Government of India to pay adequate attention towards the applications of ‘Information and Communication Technology (ICT) and its applications in irrigation water management’ for facilitating the deployment of Decision Supports Systems (DSSs) at various levels of planning and management of water resources in the country.

Digital divide commonly means the gap among diverse stakeholders, businesses, physical areas, and individual people in terms of opportunities, accessibilities, and usabilities (Acılar, 2011). Lee and Park (2011) and Barzilai-Nahon (2006) suggested that the digital divide issues should be considered as an important public issue because proper public response may enhance or reduce the information gaps by the digital divide. This study is a follow-up study of the study of Lee and Park. This study’s main aim is to clarify the changes of the digital divide in the rural areas during five years and to find out meaningful factors to reduce the gaps between the rural area and urban area. To achieve the research aim, this study analyzes the public data by ITSTAT and previous studies on the digital divide. Also this study follows the system thinking approach to model the causal relationships among diverse factors on the digital divide. With the results, this study suggests that the factors to measure the digital divide should be re-designed including smartphone penetration and accessibilities. Especially, current digital divide scoring factors should be considered in the way of social welfare.