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Although agriculture constitutes the fulcrum of economic growth and livelihood sustenance of rural farm families, particularly in developing countries, the development of the sector strongly depends on quality development and distribution of agro-innovations for adoption and integration in farm enterprise production by the farmers. According to James (1996), and Hajirostamlo, Mirsaeedghazi, Arefnia, Shariati, and Fard (2015), the thrust of transformational development of the agro-sector begins with and rests on the research institutes, basically due to their mandate to develop science-based technology(ies) that will responsively address the farming conditions of the local farmers. Emphasizing the value of research and development in agriculture, Meinzen-Dick, Adato, Haddad, and Hazell (2004) expressed that farmers would hardly be able to expand or improve their productivity without quality production resources which naturally derive from the research units. Therefore, research efforts are skewed toward the development of productive resources such as high yielding and diseases resistant crop varieties, improved breeds of livestock, and integrated management of pests and diseases of crop and livestock for the sustainable agricultural production and economic development of the farmers.
Research in agricultural development in today’s world has, however, extended beyond the applications of rudimentary methodologies or use of manually operated devices as measuring tools in research activities (Pongnumkul, Chaovalit, & Surasvadi, 2015). The rudimentary research procedures, which often take the form of conventional plant and animal breeding with accompanying physical weighing and measurement of plants and animal features for data collection, visual monitoring of plants and animal growth or response to stimuli, and manual computation of data for analysis is generally prone to errors of plus or minus against accuracy (Pavillon Agriculture, 2013). Against this approach was the integration of advanced and robust methodologies such as biotechnology and information and communication technologies (ICTs) (IFPRI, 2002). While biotechnology application takes the form of genomics, molecular breeding, bioinformatics, diagnostic, transformation, and vaccine technologies (Persley & Doyle, 2001), the ICT entails applications of digital or electronic devices which allow for accurate and efficient data monitoring and collection for analysis and charting of new course in research development.
Digital electronic devices or ICTs which mostly make use of sensors find applications in agriculture and food industry (Li, Simonian, & Chin, 2010). As further indicated by the authors, modern agricultural management makes use of different sensing technologies to provide accurate information on crop, soil, climate, and environmental conditions. Therefore, digital devices or ICTs had long been integrated in agricultural research, thereby making it possible to have fundamental and site-specific data collection which is definitely necessary for some specific decision-supports ranging from updates of weather conditions, soil nutrient status, pest management, modeling of genetic lines of plants, and livestock for adaptation to various conditions and animal production (Iwaya & Yamamoto, 2005; Zhang, Li, Zhou, & Moore, 2002).
Field applications of the digital technologies, as intensively applied in the developed countries, include the use of wireless senor networks (WSNs) and web camera for field crop imaging and monitoring of plant growths and conditions (Kouno, Roy, Machida, Moriizumi & Ninomiya, 2000; Council of Agriculture, 2012); Radio Frequency Identification (RFID) for instant livestock identification and accurate data collection on livestock (Burger, 2004; Council of Agriculture, 2012); ‘Animalprofi’ – an ultrasound scanner for pregnancy diagnosis and detections of the number of offspring in farm animals (Genetic Australia, 2016); and ‘4x4Q Mast’ digital technology for detection of animal mastitis (Dramniski n. d.).