Abstract

Some countries use agricultural information systems to assist various users, including planters, researchers, prospective buyers, importers and exporters. First apps that came to light in Mobile devices were social media and different entertainment channels. They are used extensively by the people for communication, music, entertainment, Internet and social networking. There is a lack of applications, which can be really useful for professionals to improve their working capabilities. Though people living in rural areas use mobile phones, there are hardly any relevant applications for them to improve their productivity. We are proposing to implement a farmer’s information system which can be operated on their mobile phones. Information that can be made available through such an information system includes crops and intercrops, details of their production and export, crop and intercrop diseases, availability of land, suitability for soil, fertilizer, research institutes, and research. Most of this information is in the form of statistical data and facts about these crops and products made out of them. The system is an effort to fill the gap between farmers and agricultural extension. A farmer can provide inputs related to crops being cultivated and location-specific information to get specific suggestions, alerts, and recommendations to improve productivity. And send text messages to participating farmers guiding them throughout the planting season. Whenever a farmer observes some anomalous behavior for crops or climate, the system is able to generate recommendations based on inputs provided. This digital divide may be attributed to low literacy levels, and/or ownership or control of mobile phones. The research has been conducted on the four largest villages: El Monira, Boulak, El Sherka, Nasser Al-Thawra, and Sana’a. A simple random sample of 140 respondents from the farmers’ wives (5%) was selected and chosen from the five selected villages they were 38, 33, 32, 26, 11 respectively. The final data for this research were collected through the personal interview with the respondents through a questionnaire form during July and August 2017. Pearson coefficient, the relational analysis model, and the progressive step-wise were used in analyzing the data. Numerical count, percentages, mean, and standard deviation were used to display some of the results. The services significantly influenced the farmers adobe modern agricultural methods (p<0.01). At least 40 percent of registered farmers became interested in adapting users to this program, finding it to be a reliable and accurate source of farm knowledge. Results raise two issues; firstly, how mobile services can be designed to best fit differences in gender and social realities; and secondly, how mobile services can be effectively monitored to ensure messages are being received by targeted users. It is highly beneficial to agriculturists in that it efficiently addresses real problems associated with the production of food and fiber and can help the producers develop environmentally sustainable production systems.

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