Itech7407 Real Time Analytics-Electromagnetic Radiation Assessment Answers

Answer:

Solar radiation is the power obtained from the sun per unit surface, it is in form of electromagnetic radiation. This energy can be measured in space or on the earth surface after undergoing atmospheric absorption and scattering. Plants on the earth's surface rely on the UV light derived from the sunlight to photosynthesis and so make food. The problem is that the sunlight's effect is not only the UV light but there is an accompanying issue of temperature (Scafetta & Willson, 2014).

This project will involve the analysis of sunlight exposure as measured in Ballarat airdrome. The data used for analysis will purely be secondary, derived from the Australian website with journals being used for purposes of analysis.

Being that cotton is one of the crops which is very sensitive to temperatures the data generated from the analysis will be used to model a dashboard for use by the operational manager of Brookstead farming company. The result and findings will be communicated to the Chief Executive officer of the company to make relevant adjustments.

The selected project is modelling of the monthly solar exposure. Crops need exposure to UV solar radiation for them to carry photosynthesis. This makes tropical climates to have a bigger impact on plants developments as the solar radiation access the plants for a long time. In this study, our company of focus will be Brookstead Farming Company Pty Ltd. This is a company which operates in Queensland Australia and majors in cotton farming. Having considers the influence of UV light on plants maturity the data set selected will be of importance to the company. Cotton farming is an agricultural activity which relies on effective prediction of future climatic patterns to prosper. Since cotton once planted cannot be shifted geographically to the climatic friendly areas the decision of when to plant then becomes a heavy task to the operational manager of the company. By analysing the monthly mean daily global solar exposure data, the company officials can analyse the situation and have an effective decision on when to plant and harvest the cotton (Priti Dehariya, 2011).

The monthly mean daily global solar exposure is the mean of all the daily solar energy on a surface from midnight to midnight for a period of one month. Daily solar energy values normally have a range of 1 to 35 megajoules per square meter(Australian Government Bureau of Meteorology, 2012).

Reporting

Table 1: solar exposure data in MJm^-2  (Australian government Bureau of Meteorology, 2017)

An analytical dashboard is for reporting that is useful in analysis of enormous data so that the users can easily analyse trend, predict future expectations and gain insights. The operation manager of Brookstead farming company ltd is more interested with the analyst valuation of the trends in solar exposure data for decision making, this dashboard will thereby be more effective to him.

Research

The dashboard will avail critical information at a glance to the operational manager. In other words, a dashboard can be regarded as a progress report. Its displays information to a database linked to a web page this way the report viewed from the dashboard is updated frequently. The analytical dashboard will show trend information of the solar exposure, as more verify information is fed into the website any changes in trend are reflected in the dashboard report.

The use of digital dashboard gives the operational manager capacity of monitoring the weather changes and relative improvements in productivity. As result, he will be able to identify how cotton production is affected by the weather pattern at a glance (Briggs, 2013).

There are several advantages derived from the use of analytical dashboard some of them being the performance measured is presented visually which makes interpretation of results easy. The dashboard information is updated frequently and trend well presented the operational manager is, therefore, able to detect any negative trends and take the appropriate cause of action. Since the dashboard gives information from interrelated data sets efficiencies are easily measured (Eckerson, 2010).

The operational; manager using the dashboard can generate a detailed report which indicates current issues, this has an effect in making an accurate and informed decision. The organization's goals and strategies can be aligned according to the existing situation based on=n the data at hand. This strategy gives the operational manager an easy task in implementing the strategies as factored affecting them have already been highlighted.

A quality dashboard can present communication in an uncomplicated way which is easy to understand. In addition, the distraction and confusion in the dashboard are minimised. All these together with human visual perception skills make organization of the business easy (Hetherington, 2009).

The data presented in line graphs gives a visual outlook of the trend. Since cotton production depends on the intensity of solar exposure by looking at the trend the operations manager will be able to gauge which areas will need to be worked on during a specific month.

Recommendations to CEO

The quality of cotton and quantity harvested changes depending on the weekly temperature fluctuations. This situation is more reflected in dryland cotton in which hot temperature represent high water consumption with little rainfall. Temperature effect production of cotton even in irrigation cases, for this reason, it's recommended that the production manager makes adequate plans rectify the effect as per the predicted temperature variation (Wang, et al., 2009).

From the analyzed data, the magnitude of solar exposure is high around the month of January it does, however, lowers as we move towards June. The month of June experiences the minimum solar exposure before it starts to arise towards December, January February then began lowering again. This is a periodic sequence which the operational manager should prepare for. High solar exposure affects both the temperatures and UV light which are all factors in the production of cotton.

Hot temperature decreases photosynthesis and triggers high respiration rate this make the seed production process to slow down, also the lint development is hindered. All this add to lead to poor lower quantity produced. Despite cotton having the ability to retain canopy temperature lower than the surrounding air temperature increased humidity combined with high air temperature could result in canopy temperature which is above the optimum level. When the temperature is high during the day the rate of photosynthesis is reduced at night respiration will be high combining to reduce productivity. Plants manufacture the same number of bolls but with fewer seeds. This means smaller bolls and reduced lint production (Chapagain, Hoekstra, Savenije, & Gautam, 2006).

When growing cotton without irrigation there is a potentiality of hedging lower yield production through a selection of more heat tolerant cotton varieties. Though the company may need to do research on information of cotton species regarded as heat tolerant, also, the planting dates can be stretched or even planting varieties which may mature faster before the temperatures heat their peak. When these factors are accounted for then the firm suffers less risk in terms of cotton production quantity and quality (Loka, 2016).

Being that the manager will have an influence on those who access the data from the dashboard the operations manager will be able to communicate his position to the employees in a way which can be easily be illustrated and understood, this way the employees will be able to operate in a uniform platform having sufficient information to pursue the firm's targets.

 Brookstead Farming Company Pty Ltd

Branchview

Brookstead, QLD, Australia

Dear Mr/ Ms

RE: Production data insight

Having undertaken a research work on solar exposure and its effects in cotton production there are issues that I would like to bring your attention to.

Data analysis noted that the intensity of the sunlight radiation was very high from the months of December to March, subsequently, there is a general low solar exposure around the month of June. I would wish to take into account those factors when organizing for the planting session. Furthermore, efforts should be put in place to ensure that the current crops in the field are adequately watered during the months of December to March to try minimising the hot temperatures dangers on the crops.

Finally, to assist in your future decision making I recommend your farm adopt the use of analytical dashboard in accessing and analyzing relevant information needed for decision-making. The tool is efficient in availing information instantly at your request since it can be attached to several websites and the firm's database the information gained from it is frequently updated based on the occurring changes the outcome is efficient, reliable and up to date data which gives you an opportunity to make very informed decisions

References

Australian Government Bureau of Meteorology. (2012). Solar Radiation Definitions. Retrieved September 29, 2017, from https://www.bom.gov.au/climate/austmaps/solar-radiation-glossary.shtml#globalexposure

Australian government Bureau of Meteorology. (2017, September 29). Australian government Bureau of Meteorology. Retrieved from Monthly mean daily global solar exposure: https://www.bom.gov.au/jsp/ncc/cdio/weatherData/av?p_nccObsCode=203&p_display_type=dataFile&p_startYear=&p_c=&p_stn_num=089002

Briggs, J. (2013). Management Reports & Dashboard Best Practice. Target Dashboard.

Chapagain, A. K., Hoekstra, A. Y., Savenije, H. H., & Gautam, R. (2006). The water footprint of cotton consumption: An assessment of the impact of worldwide consumption of cotton products on the water resources in the cotton producing countries. Ecological Economics, 196–203.

Eckerson, W. W. (2010). Performance Dashboards: Measuring, Monitoring, and Managing Your Business. Wiley.

Hetherington, V. (2009). Dashboard Demystified: What is a Dashboard? Hetherington.

Loka, D. a. (2016). Increased night temperatures during cotton's early reproductive stage affect leaf physiology and flower bud carbohydrate content decreasing. Journal of Agronomy and Crop Science, 900-2100.

Priti Dehariya, S. K. (2011). NCBI: Assessment of impact of solar UV components on growth and antioxidant enzyme activity in cotton plant. Retrieved September 28, 2017, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3550570/

Scafetta, N., & Willson, R. C. (2014). ACRIM total solar irradiance satellite composite validation versus TSI proxy models. Astrophysics and Space Science, 400-441.

Wang, Z., Lin, H., Huang, J., Hu, R., Rozelle, S., & Pray, C. (2009). Bt Cotton in China: Are Secondary Insect Infestations Offsetting the Benefits in Farmer Fields?". Agricultural Sciences in China, 73–90.