Improving Australian Precision Agriculture - Case Study Example

RESEARCH PROPOSAL: IMPROVING PRECISION AGRICULTURE IN AUSTRALIA By Student’s Name Code + Name of Course Professor/Tutor Institution City/State Date Improving Australian Precision Agriculture Abstract: The climate of Australia is relatively arid conditions, greatly weathered soils, averagely huge farmland mass that generates little farm revenue. An ever-rising population globally and progressively unstable commodity costs have made farmers with the duty of being more effective. These unique situations naturally suit the integration of precision agriculture (PA) into farm management. PA is a relatively new concept, which Australian farmers can consider as a way of improving efficiencies in resource uses with risk environmental and risk management advantages following. However, the adoption of the technologies is very limited. This research will use a qualitative method grounded on a literature study and a survey to respond to the question of the potential strengths, weaknesses, opportunities, and threats of PA adoption and the related questions. By responding to these questions, the current study will contribute to the available studies and will assist in improving the broad acre cropping system and subsequently the Australian Agriculture sector. 1.0. Introduction The concept of Precision Agriculture has different meanings to the agricultural community of Australia. The many definitions of PA suggest different ideas to different people across the world over the real meaning of the agricultural concept. Nonetheless, the core of PA is that indorsing timely and necessary measures to variables in agricultural productivity will generate social-economic and environmental paybacks. The American House of Representatives has provided a more precise definition, which mirrors this philosophy (US House of Representatives 2007, pg. 14). In their definition, PA is a production-grounded and integrated information system of agriculture, which is established to improve long term, site-particular efficiency in farm production, yield, and profitability whilst reducing unintended effects on the environment and wildlife. Several studies have documented the economic gains of directions for chemical application and tramline farming. More research on PA adoption among farmers is ongoing. This study seeks to document the present status of PA within the Australian broad acre cropping system and report the advantages, opportunities, and challenges presented by these technologies. In specific, the study assesses the rates of adapting new equipment and farming methods. The study also examines the potential of incorporating different PA components to improve productivity as well as a documentation of the perceptions and experiences of farmers with the technology through a survey. The paper generally covers different perspectives of issues linked to Precision Agriculture and a recommendation for future research. 1.1. Scope of the Study This study will examine the issues related with adoption of PA within Australia through a literature-based study where academic articles, which discuss the issues will be examined. In addition, the study will conduct a survey among farmers in Nebraska to find out their perceptions and experience with using PA. 1.2. Research Questions This inquiry seeks to answer different questions comprising: i) What are the potential strengths and opportunities associated with using PA in ensuring production efficiency ii) How is the future outlook of precision agriculture in making Australian Agriculture more financial enticing? iii) Why is the adoption of PA low among Australian Farmers? iv) How can farmers be assisted to increase their agricultural output? 2.0. Literature Review Australia is a comparatively dry continent with different kinds of soils, which are typically ancient, relatively less fertile and immensely. The latest census stated that it has a population of 21 million individuals with only about 4 % of the entire workforce being employed directly in the agricultural industry. About 58 % of the total land mass is under agricultural productivity. About 27 % of the agricultural land is under crop production with the wide part used for animal grazing (Australian Bureau of Statistics (ABS) 2007, pg. 13). Land under irrigation with both plants and pastures represent below one percent of the entire landmass under agricultural productivity. A portion of the entire 129,950 agri-business creativities in 2012, broad acre businesses were approximately 42,000 in number. Under these economic and physical and situations, the Australian agriculture sector ought to uphold a high self-sustainability level and efficiency to contest in the global agricultural business. Lately, there have been changes in the affordability and accessibility to systems of machinery guidance, variable rate applicators, yield monitors, and different tools of data collection comprising electromagnetic soil surveys and satellite imagery (White 2006, pg. 18). These innovations are collectively called PA. The application of PA is an opening for improving the effectiveness with which fertilizers and other pest control measures are used. These collectively have the potential of improving farm productivity and minimizing the ecological effect of agricultural productivity (Jochinke, Noonon, Wachsmann, & Norton 2007, pg. 70). Several studies have presented the benefits associated with using PA to enhance agricultural productivity. In a case study on the economic paybacks of precision agriculture by Robertson, Carberry, and Brennan (2007, pg. 3), it was established that farmers who used PA technologies minimized their environmental effects and enhanced their productivity and profitability simultaneously. This study further documents that compared to about twenty years ago, machinery and tractors have not just increased in accuracy, number, and effectiveness as farming inputs but can presently function systems of farming such as drilling seeds into farms while the erect stubbles from the former plants in place. The case study methodology adopted by this study is important because similar to our current study, the case studies selected in this study covered a range of systems of cropping, field sizes, and yield levels in the broadacre practicing areas of Australia. A different case study by Watcharaanantapong (et al., 2014, pg. 428) reinforces this study by emphasizing the importance of PA application in America. These case studies are important as they provide the direct benefits associated with using PA in agriculture from the farmer’s perspective. The discussions of these studies clearly suggest that apart from minimizing inputs through the enhanced precision of the technologies, PA innovations allows growers to increase productivity from using the huge volume of information availed to them and these prospective benefits could allow them to get more yield using less inputs. Another survey study by Castle, Lubben and Luck (2016, pg. 3), found that the variables influencing the adoption of PA included average farm income, operator age, number of acres under agriculture, irrigation use and the farmer’s use of a cellular phone with access to the internet. Thus, the survey allowed the researchers to established that farmers in the area acknowledged that the process of information collection linked with the SSCM adaptation (Site Specific Crop Management) of the PA system generally augments the knowledge of the manager of each farm. This study supports our current research because comprehending the trends and causes of variability in produce within farms is likely to improve the farmers’ choices on crop selection and the management of agronomics or alternate land uses. In Castle, Lubben and Luck’s study, (2016, pg. 6), the growers still considered yield maps as a great source of information. From the survey, it was realized that even modest information comprising bare soil aerial imagery assisted farmers identifies the level of intrafield difference and thus decide on issues that concern the worthiness of farm zoning. This kind of analysis assisted in identifying chemical or physical soil restrictions, which are certainly manageable with the appropriate fertilizer use practices thereby improving returns. In an interview with farmers, a study by Smith (et al., 2015, pg. 185) found that many growers in India consider PA as interesting. However, the study found that adoption requires that there is objective to seek finances for adopting the innovation especially provided the unpredictable weather conditions experienced in the country. The assessment demonstrated that taking up the primary SSCM model added approximately $ 20 per hectare or 98% to averagely input expenses on a farmland of 1000 hectares. A literature review study replicates the aims of our current study. Nash, Korduan, and Bill (2009, pg. 550) found that even though expertise in PA has been present in the country for over ten years, only about three per cent of grain farmers in Australia are applying some type of the innovation. There has been a suggestion that the reason for low PA adoption is the farmers’ reluctance to invest more money in Precision Agriculture without the knowledge of whether the technology will be profitable or not. Similarly to Robertson, Carberry, and Brennan’s studies, (2007, pg. 6), farmers expressed doubt over the investment worthiness of the PA venture. According to Nash, Korduan, and Bill (2009, pg. 550), early adopters of PA often incur extraordinary costs with their capital expenses reaching $60 000. The figure is seemingly too high for potential PA adopters making them deliberative over the application of PA in farms. In the country, the original users usually plant in huge fields (more than 3000 hectares) suggesting greatly precise auto-steer (2cm) models represent an appropriate venture grounded on 10 per cent save in agricultural inputs with less overlay (Nash, Korduan, and Bill 2009, pg. 551). Expenses of GPS could span from 900-25,000 $ in tandem with the precision that fits the undertaking. A different primary research study documented that the latest significant increases in fuel and fertilizer prices ensure that the advantages of adapting the Precision Agriculture innovation lend more financial allure, particularly in the broad acre sector (Ahmadi 2008, pg. 18). Ecological considerations and decisions will be made as the political landscape changes to mirror wider concerns of the society. In line with our study, this study reinforces the fact that this alongside the expectation to derive more benefit from management of PA hardware will ensure more application of variable-rate innovations across the country. Provided that the main restricting factor in most segments of the agricultural sector in soil moisture, the capacity to measure the capacity of moisture in soil as well as soil moisture composition in all fields will be of boundless advantage. There are ongoing studies into measuring AWC with more simple soil geophysical measures. Clearly, the instantaneous measures of soil content measures in the farms would hugely augment the capacity of managing soil chemistry in accurate ways. The creation of these sensing models is ongoing in the country (Ahmadi 2008, pg. 20). Australian farmers will start to obtain quality data on their products to a higher degree to ensure that input management can be custom-made to increase quantity and quality production. Sensors for measuring quality parameters comprising sugar content (cane, grapes); protein (cereals); oil (corn, rapeseed) will be used more predominantly. The entire PA concept will be stretched extensively to wholesome field management as well as on on-field work. Several growers in the country are following keenly the use of historical data generation with real-time information of crops (for instance Greenseeker; Yarra N-Sensor) in managing nitrogen farming inputs. This has the potential of making application decisions more responsive to seasons and minimizes financial risk to a huge extent. Finally, future research bodies and funding organizations should devote to longer-term investments, which incorporate PA methods use and identify appropriate agro-economic measures in the management of spatial variability in the Australian grain-producing sector. Consequently, an all-inclusive approach that involves the scientists, farmers, and stakeholders in the industry is critical. 3.0. Research Methods 3.1. Research Process This study will adopt a qualitative study approach comprising the use of a literature review study and a survey to respond to the questions associated with PA adoption. The survey will help to comprehend the objective of Precision Agriculture as well as challenges to adoption. The survey will use a cross-sectional design in which samples of farmers will be drawn once from Nebraska in rural Australia where broad acre cropping system is used. The surveys will be distributed to twenty (20) farmers at the annual Nebraska Agricultural Extension sponsored event. The farmers will be selected by convenience sampling based on their willingness to participate in the study. The main assumption here is that the growers attending the Extension event may be conversant with new technologies for use in agriculture (Castle, Lubben, and Luck 2016, pg. 5). The surveys will cover different areas that assess the current penetration of PA into systems of farming and the farmers’ perceptions to these technologies. The survey will optimize open-ended questionnaires as tools of collecting data. The survey answers will be recorded for later analysis. The advantage of using open-ended questionnaire is that the unclear questions will be explained to the farmers while the data collectors will record down upcoming issues and revise the questions as necessary (Hennink, Hutter and Bailey 2010, pg. 113). The vocabulary used in the questions will be simple and direct to facilitate the farmers’ responses. The literature review comprises the use of different libraries and search engines to locate appropriate academic information available on PA application. The articles uses are reputable and with information no further than 2006. The relevant articles are categorized based on their relevance to the research questions. Data will be analysed through content (thematic) analysis wherein resultant themes and classes from data will be identified. The procedure will encompass identifying themes in the survey sheets with attempts to validating, qualifying and grouping them. The process is repeated to determine more themes and classes as they relate to the research questions. 3.2. Research Plan/Timetable Research Step Number of weeks/days needed Commencing date Close date STAGE one: Study and research a) Searching for an unique and manageable topic 1 day 25/10/2016 25/10/2016 b) Researching and studying into selected issue 1 day 26/10/2016 26/10/2016 STAGE two: The comprehensive strategy a) Development of a comprehensive strategy of the proposal 1 day 27/10/2016 27/10/2016 STAGE 3: First writing a) Drafting the various sections of the proposal 2 days 28/10/2016 29/10/2016 b) Conducting more research where necessary 1 day 28/10/2016 28/10/2016 STAGE 4: The first draft a) Compile and collate sections into the proposal’s first draft 2 days 29/11/2016 30/11/2016 b) Checking the proposal’s flow 1 day 30/11/2016 30/11/2016 c) Checking the length of the proposal 1 day 31/10/2016 31/10/2016 d) Carrying out any extra editing and research 1 day 1/11/2016 1/11/2016 STAGE 5: Final draft a) Crosschecking for errors 1 day 2/11/2016 2/11/2016 b) Preparation for submission 1 day 2/11/2016 2/11/2016 c) Final proof-reading 1 day 3/11/2016 3/11/2016 d) Compilation of bibliography 1 day 3/11/2016 3/11/2016 e) ) Submission of my proposal 1 day 4/11/2016 4/11/2016 Reference List Ahmadi, M 2008, ‘Precision agriculture,’ Journal of Agricultural Jihad Message, Vol. 78, pp.18-19. Castle, M.H, Lubben, BD. and Luck, JD 2016, ‘Factors Influencing the Adoption of Precision Agriculture Technologies by Nebraska Producers,’ pp. 2-25. Australian Bureau of Statistics (ABS) 2007. Year Book Australia, 2007. Available from: www.abs.gov.au. [Accessed 26 Oct. 2016]. Hennink, M., Hutter, I. and Bailey, A., 2010. Qualitative research methods. Sage. Jochinke, DC, Noonon, BJ, Wachsmann, NG and Norton, RM 2007, ‘The adoption of precision agriculture in an Australian broadacre cropping system—Challenges and opportunities,’ Field Crops Research, Vol. 104, no. 1, pp.68-76. Nash, E, Korduan, P and Bill, R 2009, ‘Applications of open geospatial web services in precision agriculture: a review,’ Precision agriculture, Vol.10, no. 6, pp.546-560. Robertson, M., Carberry, P. and Brennan, L., 2007, ‘The economic benefits of precision agriculture: case studies from Australian grain farms,’ CSIRO, Vol. 12, pp. 1-46. Smith, CM, Dhuyvetter, KC, Kastens, TL, Kastens, DL and Smith, LM 2013, ‘Economics of Precision Agricultural Technologies Across the Great Plains 2013,’ Journal of the ASFMRA, pp.185-206. US House of Representatives 2007. An Act to reform, extend and repeal certain agricultural research, extension and education programs and for other purposes. Title IV - New research, extension, and education initiatives. Subtitle B - Precision Agriculture. Available from: [Accessed 26 Oct. 2016]. Watcharaanantapong, P, Roberts, RK, Lambert, DM, Larson, JA, Velandia, M, English, BC, Rejesus, RM. and Wang, C, 2014, ‘Timing of precision agriculture technology adoption in US cotton production,’ Precision agriculture, Vol. 15, no. 4, pp.427-446. White, B., 2006, ‘Affordable gear sees guidance use double,’ Farming Ahead, Vol. 171, p.18. Read More